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/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention

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PROMPT.txt
benchmark.py
check.py
problem.yaml
reference.py
shapes.py
sota.py

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PROMPT.txt
shapes.py
sota.py
reference.py
check.py
benchmark.py
problem.yaml

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## master...origin/master

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96b597e qwen3.6-27b reinstated: 1/7 PASS in post-fix rerun
5722a4a opencode workspace leak: deny external_directory + drop qwen3.6-27b
50ecc7a Shakedown sweep results + drop qwen3.6-35b-a3b from active matrix

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Filesystem      Size  Used Avail Use% Mounted on
/dev/nvme0n1p2  3.6T  1.8T  1.7T  51% /

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uv 0.11.3 (x86_64-unknown-linux-gnu)

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Python 3.11.15

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Output:
Mon Apr 27 23:54:32 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   31C    P3             44W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

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Output:
"""Naive PyTorch paged-attention decode reference (correctness oracle, not SOTA).

Single-query decode: each batch element has a query of shape (num_heads, head_dim)
and attends over a KV cache of `seq_len[b]` tokens stored as fixed-size pages in
a global pool. Pages for batch element b are listed in `block_table[b]`.

The reference performs the slow path:
  1. Gather pages -> contiguous (seq_len, num_kv_heads, head_dim) per batch element.
  2. Repeat KV heads for grouped-query (broadcast num_kv_heads -> num_heads).
  3. Manual softmax(QK^T / sqrt(d)) @ V in fp32, cast back to bf16.

This avoids torch.nn.functional.scaled_dot_product_attention (which is on the
forbidden list) so the agent cannot dispatch through SDPA either.
"""
import math

import torch
import torch.nn as nn

OP_TYPE = "attention"
SUPPORTED_PRECISIONS = ["bf16"]
HARDWARE_REQUIRED = ["RTX_PRO_6000", "H100", "B200"]


# --- Shape knobs (overridden by check.py / benchmark.py from shapes.py) ----
BATCH = 8
NUM_HEADS = 32
NUM_KV_HEADS = 8
HEAD_DIM = 128
SEQ_LEN = 1024
PAGE_SIZE = 16


class Model(nn.Module):
    """Single-query paged attention decode.

    Forward inputs (all on device):
      query:       (batch, num_heads, head_dim)               bf16
      kv_cache:    (num_blocks, page_size, num_kv_heads, head_dim * 2)
                   Layout: last dim packs [K | V] so a single gather pulls both.
       

... (3756 more chars)

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"""Correctness runner for paged-attention decode.

Runs solution.Model vs reference.Model across all shapes in shapes.py, 3 seeds
each, with per-dtype atol/rtol. Also rejects forbidden ops by grep.
"""
import re
import sys
from pathlib import Path

import torch
import yaml

REPO_ROOT = Path(__file__).resolve().parents[2]
sys.path.insert(0, str(REPO_ROOT))

from src.eval.correctness import check_correctness  # noqa: E402


def _apply_shape(reference, shape: dict) -> None:
    reference.BATCH = shape["batch"]
    reference.NUM_HEADS = shape["num_heads"]
    reference.NUM_KV_HEADS = shape["num_kv_heads"]
    reference.HEAD_DIM = shape["head_dim"]
    reference.SEQ_LEN = shape["seq_len"]
    reference.PAGE_SIZE = shape["page_size"]


def main():
    try:
        import reference
        import shapes
        import solution
    except Exception as e:
        print(f"FAIL: import error: {e}")
        sys.exit(1)

    problem_yaml = Path("problem.yaml")
    meta = yaml.safe_load(problem_yaml.read_text()) if problem_yaml.exists() else {}

    sol_src = Path("solution.py").read_text() if Path("solution.py").exists() else ""
    for forbidden in meta.get("forbidden", []):
        pat = re.escape(forbidden)
        if re.search(pat, sol_src):
            print(f"FAIL: forbidden op used: {forbidden}")
            sys.exit(1)

    device = torch.device("cuda:0")
    tol_override = meta

... (2045 more chars)

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"""Roofline benchmark for paged-attention decode.

For each shape: times eager reference, compiled reference, SOTA (if available),
and the agent's solution. Reports achieved TFLOPS, GB/s, and peak_fraction.

Decode is memory-bound, so peak_fraction is computed from achieved GB/s vs
the GPU's peak DRAM bandwidth.
"""
import sys
from math import exp, log
from pathlib import Path

import torch
import yaml

REPO_ROOT = Path(__file__).resolve().parents[2]
sys.path.insert(0, str(REPO_ROOT))

from src.eval.roofline import compute_gbps, compute_tflops, peak_fraction  # noqa: E402
from src.eval.timing import time_fn  # noqa: E402
from src.hardware import get as get_hw  # noqa: E402


def _eval_formula(expr: str, vars: dict) -> float:
    return float(eval(expr, {"__builtins__": {}}, vars))


def _apply_shape(reference, shape: dict) -> None:
    reference.BATCH = shape["batch"]
    reference.NUM_HEADS = shape["num_heads"]
    reference.NUM_KV_HEADS = shape["num_kv_heads"]
    reference.HEAD_DIM = shape["head_dim"]
    reference.SEQ_LEN = shape["seq_len"]
    reference.PAGE_SIZE = shape["page_size"]


def main():
    import reference
    import shapes
    import solution

    meta = yaml.safe_load(Path("problem.yaml").read_text())
    hw = get_hw(meta["hardware"][0])
    peak_tflops = hw.peak_tflops_dense.get(meta["peak_tflops_key"], 0.0)
    peak_gbps = hw.peak_bandwidth_gb_s
    re

... (2958 more chars)

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Output:
"""Shape sweep for paged attention decode.

Mix targets:
  - small batch / long context (Llama-3 8B-style decode)
  - large batch / medium context (server batched decode)
  - GQA wide ratio (Llama-3 70B: 64 heads / 8 kv-heads)
  - non-power-of-2 seq_len (forces predicated tail handling)
  - head_dim=64 small-head case
"""

SHAPES = [
    # (B, H, Hkv, D, L, P)
    {"batch": 8,  "num_heads": 32, "num_kv_heads": 8,  "head_dim": 128, "seq_len": 1024, "page_size": 16},
    {"batch": 32, "num_heads": 32, "num_kv_heads": 8,  "head_dim": 128, "seq_len": 2048, "page_size": 16},
    {"batch": 4,  "num_heads": 64, "num_kv_heads": 8,  "head_dim": 128, "seq_len": 4096, "page_size": 16},
    {"batch": 16, "num_heads": 32, "num_kv_heads": 8,  "head_dim": 128, "seq_len": 1535, "page_size": 16},  # non-pow2
    {"batch": 8,  "num_heads": 16, "num_kv_heads": 4,  "head_dim": 64,  "seq_len": 2000, "page_size": 16},  # small-D, non-pow2
]

Chunk ID: 37c487
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Output:
name: 03_paged_attention
display_name: "Paged Attention Decode"
precision: bf16
regime: memory  # decode is bandwidth-bound (KV cache streamed once per token)

# Effective FLOPs per call: QK^T + softmax*V across all batches/heads/seq.
# Sum-formula evaluated per-shape; the benchmark substitutes batch/num_heads/etc.
# 2 * B * H * L * D for QK^T plus 2 * B * H * L * D for AV  =>  4 * B * H * L * D
flops_formula: "4 * batch * num_heads * seq_len * head_dim"

# Bytes moved (the real bottleneck): the KV cache must be streamed end-to-end.
#   K and V each:  batch * seq_len * num_kv_heads * head_dim * 2 bytes (bf16)
#   Q: batch * num_heads * head_dim * 2  (negligible vs KV)
#   Out: same as Q
# So total ~ 2 * (B * L * Hkv * D * 2) + small.
bytes_formula: "2 * batch * seq_len * num_kv_heads * head_dim * 2 + batch * num_heads * head_dim * 2 * 2"

hardware: [RTX_PRO_6000]
peak_tflops_key: bf16          # informational; regime=memory uses bandwidth
peak_bandwidth_key: dram        # 1.8 TB/s GDDR7 on RTX PRO 6000 Blackwell

tolerance:
  bfloat16: 0.02
  float16: 0.02

# Forbidden ops -- using any of these in solution.py fails correctness post-hoc.
# vllm.attention / flashinfer.batch_decode_with_paged_kv_cache: dispatching to
# the SOTA library is the trivial cheat. SDPA is also banned because the agent
# could gather pages then call SDPA and inherit FlashAttention "for free".
forbidde

... (634 more chars)

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Output:
"""SOTA reference for paged-attention decode.

Tries, in order:
  1. FlashInfer's BatchDecodeWithPagedKVCacheWrapper (preferred -- portable,
     supports SM120, GQA, arbitrary head_dim).
  2. vLLM's paged_attention_v2 CUDA op (requires its KV-cache layout, more
     finicky; we adapt the layout on the fly when possible).

If neither is importable, is_available() returns False and the benchmark just
reports eager + compiled + solution.

Agents are FORBIDDEN from importing these in solution.py (see problem.yaml).
This file is only for the benchmark's reference line.
"""
from __future__ import annotations

import torch


def _try_flashinfer(
    query: torch.Tensor,
    kv_cache: torch.Tensor,
    block_table: torch.Tensor,
    seq_lens: torch.Tensor,
    num_kv_heads: int,
    head_dim: int,
    page_size: int,
) -> torch.Tensor | None:
    try:
        import flashinfer  # noqa: F401
        from flashinfer.decode import BatchDecodeWithPagedKVCacheWrapper
    except Exception:
        return None

    B, H, D = query.shape
    # FlashInfer expects K and V as separate (num_blocks, page_size, num_kv_heads, head_dim) tensors.
    # Our reference packs [K|V] on the last dim -- split here.
    k_cache = kv_cache[..., :D].contiguous()
    v_cache = kv_cache[..., D:].contiguous()

    workspace = torch.empty(128 * 1024 * 1024, dtype=torch.uint8, device=query.device)
    wrapper = 

... (1423 more chars)

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Chunk ID: 08c33a
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Output:
2.11.0+cu130
13.0
(12, 0)

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Output:
3.6.0

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Output:
"""Centralized GPU timing for benchmark.py files.

All problems' benchmark.py should call `time_fn` from here so we have one
implementation of warmup, L2 flush, and CUDA event capture to maintain.

Methodology:
  - 10 warmup calls absorb Triton autotune (typical ~7 configs) and
    torch.compile reduce-overhead CUDA-graph capture.
  - Between each timed call, `_l2_flush()` writes 128 MB to evict L2
    (Blackwell L2 is 96 MB; we want any prior L2 contents flushed so
    we measure HBM-load bandwidth, not L2-cached bandwidth).
  - GPU timing via cuda.Event with synchronize() AFTER record() but
    BEFORE elapsed_time() — the canonical NVIDIA pattern.
  - Reported value is the median of `iters` trials, robust to outliers.

Notes / known biases not addressed here:
  - torch.compile(mode="reduce-overhead") gets CUDA graphs which eliminate
    launch overhead. Custom Triton/CUDA kernels do NOT get this treatment.
    On small shapes where launch overhead matters, this gives compile an
    artificial advantage. We accept this as the cost of using the agreed
    "compiled" baseline policy.
  - cuBLAS / cuDNN allocate workspaces on first call. 10 warmup absorbs.
  - Median over a fairly small number of trials (default 30) is fine for
    headline numbers but won't catch bimodal distributions. Use --extra
    instrumentation if you ever care.
"""
from __future__ import annotations



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"""Per-dtype correctness tolerance.

Stanford's KernelBench uses 1e-4 atol/rtol for fp32 and 1e-2 for fp16/bf16.
We extend to fp8 (0.1, permissive) and int (exact).
"""
from __future__ import annotations

import torch

DEFAULT_TOLERANCE = {
    torch.float32: {"atol": 1e-4, "rtol": 1e-4},
    torch.float16: {"atol": 1e-2, "rtol": 1e-2},
    torch.bfloat16: {"atol": 1e-2, "rtol": 1e-2},
    torch.float8_e4m3fn: {"atol": 1e-1, "rtol": 1e-1},
    torch.float8_e5m2: {"atol": 1e-1, "rtol": 1e-1},
    torch.int8: {"atol": 0, "rtol": 0},
    torch.int32: {"atol": 0, "rtol": 0},
    torch.int64: {"atol": 0, "rtol": 0},
}


def _coerce_float(x):
    """Accept int/float/str scientific-notation as float; pass through dicts."""
    if isinstance(x, (int, float)):
        return float(x)
    if isinstance(x, str):
        try:
            return float(x)
        except ValueError:
            return x
    return x


def tolerance_for_dtype(dtype: torch.dtype, override: dict | None = None) -> dict:
    """Lookup atol/rtol for a given dtype, with optional per-problem override.

    The override dict is keyed by str(dtype). Values may be:
      - a single number (or a string parseable as float, e.g. "5e-2") -> used
        as both atol and rtol
      - a dict {"atol": ..., "rtol": ...} -> used directly, with values coerced
    """
    # Accept several spellings of the same dtype key (PyYAM

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Output:

output:
  Success. Updated the following files:
  A /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: 833138
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:56:18 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   30C    P5             26W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: f00b75
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Output:

Chunk ID: be0a35
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Output:

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Output:
PASS

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Original token count: 492
Output:
Mon Apr 27 23:56:38 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   30C    P5             34W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

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Output:

Chunk ID: 4284b8
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Original token count: 846
Output:
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break from `Tensor.item()`, consider setting:
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     torch._dynamo.config.capture_scalar_outputs = True
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] or:
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] to include these operations in the captured graph.
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] 
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break: from user code at:
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]   File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/reference.py", line 89, in forward
W0427 23:56:42.188000 1336652 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     L = int(seq_lens[b].item())
W0427 23:56:42.1

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Chunk ID: c69b62
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:57:18 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   31C    P8             11W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 358a96
Wall time: 0.5990 seconds
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Original token count: 412
Output:
Traceback (most recent call last):
  File "/home/infatoshi/cuda/KernelBench-Hard/.venv/lib/python3.11/site-packages/triton/runtime/jit.py", line 461, in __init__
    self.raw_src, self.starting_line_number = inspect.getsourcelines(fn)
                                              ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/infatoshi/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/inspect.py", line 1240, in getsourcelines
    lines, lnum = findsource(object)
                  ^^^^^^^^^^^^^^^^^^
  File "/home/infatoshi/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/inspect.py", line 1077, in findsource
    raise OSError('could not get source code')
OSError: could not get source code

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 5, in <module>
  File "/home/infatoshi/cuda/KernelBench-Hard/.venv/lib/python3.11/site-packages/triton/runtime/jit.py", line 935, in jit
    return decorator(fn)
           ^^^^^^^^^^^^^
  File "/home/infatoshi/cuda/KernelBench-Hard/.venv/lib/python3.11/site-packages/triton/runtime/jit.py", line 923, in decorator
    return JITFunction(
           ^^^^^^^^^^^^
  File "/home/infatoshi/cuda/KernelBench-Hard/.venv/lib/python3.11/site-packages/triton/runtime/jit.py", line 756, in __init__
    super().__init__(fn)
  File "/home/infa

... (252 more chars)

output:
  Success. Updated the following files:
  A /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/dot_test.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: 309816
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:57:34 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   31C    P0             49W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 9bef2f
Wall time: 1.0010 seconds
Process running with session ID 36175
Original token count: 19
Output:
ok 4 -15.073624610900879
ok 8 -7.866250514984131
ok 16 -2.937061309814453

Chunk ID: 032630
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 0
Output:

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: 3c6e5d
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:58:05 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   30C    P8             15W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 20f7f7
Wall time: 1.0011 seconds
Process running with session ID 29358
Original token count: 0
Output:

Chunk ID: 4aa1c3
Wall time: 5.0010 seconds
Process running with session ID 29358
Original token count: 0
Output:

Chunk ID: 7d1bf1
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 2
Output:
PASS

Chunk ID: 4847f0
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:58:23 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   31C    P5             48W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 3dcb95
Wall time: 1.0011 seconds
Process running with session ID 4016
Original token count: 0
Output:

Chunk ID: 0e4618
Wall time: 3.5978 seconds
Process exited with code 0
Original token count: 846
Output:
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break from `Tensor.item()`, consider setting:
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     torch._dynamo.config.capture_scalar_outputs = True
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] or:
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] to include these operations in the captured graph.
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] 
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break: from user code at:
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]   File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/reference.py", line 89, in forward
W0427 23:58:27.651000 1338017 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     L = int(seq_lens[b].item())
W0427 23:58:27.6

... (1988 more chars)

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: 453eb5
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:58:55 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   31C    P8             15W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 030417
Wall time: 1.0004 seconds
Process running with session ID 16990
Original token count: 0
Output:

Chunk ID: 6248cb
Wall time: 5.0026 seconds
Process running with session ID 16990
Original token count: 0
Output:

Chunk ID: 18d832
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 2
Output:
PASS

Chunk ID: 7652d7
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:59:11 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   32C    P0             52W /  600W |     508MiB /  97887MiB |      3%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: b1bd0d
Wall time: 1.0008 seconds
Process running with session ID 23759
Original token count: 0
Output:

Chunk ID: fe3632
Wall time: 3.5112 seconds
Process exited with code 0
Original token count: 846
Output:
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break from `Tensor.item()`, consider setting:
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     torch._dynamo.config.capture_scalar_outputs = True
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] or:
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] to include these operations in the captured graph.
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] 
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break: from user code at:
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]   File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/reference.py", line 89, in forward
W0427 23:59:15.287000 1338748 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     L = int(seq_lens[b].item())
W0427 23:59:15.2

... (1988 more chars)

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: 803217
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:59:24 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   33C    P3             46W /  600W |     508MiB /  97887MiB |      3%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 8e18e1
Wall time: 1.0011 seconds
Process running with session ID 60667
Original token count: 0
Output:

Chunk ID: c7662f
Wall time: 5.0013 seconds
Process running with session ID 60667
Original token count: 0
Output:

Chunk ID: d036b5
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 2
Output:
PASS

Chunk ID: efaef2
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:59:40 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   33C    P0             50W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 6bfbcd
Wall time: 1.0014 seconds
Process running with session ID 85298
Original token count: 0
Output:

Chunk ID: 777ed9
Wall time: 3.3605 seconds
Process exited with code 0
Original token count: 846
Output:
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break from `Tensor.item()`, consider setting:
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     torch._dynamo.config.capture_scalar_outputs = True
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] or:
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] to include these operations in the captured graph.
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] 
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break: from user code at:
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]   File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/reference.py", line 89, in forward
W0427 23:59:44.146000 1340917 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     L = int(seq_lens[b].item())
W0427 23:59:44.1

... (1988 more chars)

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: 930558
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Mon Apr 27 23:59:53 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   33C    P3             47W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 76d60a
Wall time: 1.0012 seconds
Process running with session ID 90205
Original token count: 0
Output:

Chunk ID: 3db3fc
Wall time: 0.0000 seconds
Process exited with code 1
Original token count: 548
Output:
Traceback (most recent call last):
  File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/check.py", line 109, in <module>
    main()
  File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/check.py", line 72, in main
    sol_out = sol_model(*inputs)
              ^^^^^^^^^^^^^^^^^^
  File "/home/infatoshi/cuda/KernelBench-Hard/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/infatoshi/cuda/KernelBench-Hard/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py", line 185, in forward
    _paged_attn_decode_grouped_kernel[grid](
  File "/home/infatoshi/cuda/KernelBench-Hard/.venv/lib/python3.11/site-packages/triton/runtime/jit.py", line 370, in <lambda>
    return lambda *args, **kwargs: self.run(grid=grid, warmup=False, *args, **kwargs)
                                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/infatoshi/cuda/KernelBench-Hard/.venv/lib/python3.11/site-packages/triton/runtime/jit.py", line 743, in run
    launch_metadata = kernel.launch_metadata(grid, s

... (795 more chars)

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: bd28e9
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:00:18 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   32C    P8             11W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: f4d2bb
Wall time: 1.0011 seconds
Process running with session ID 20931
Original token count: 0
Output:

Chunk ID: 5aa853
Wall time: 5.0014 seconds
Process running with session ID 20931
Original token count: 0
Output:

Chunk ID: 9bd00a
Wall time: 1.1097 seconds
Process exited with code 0
Original token count: 2
Output:
PASS

Chunk ID: b4a3a0
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:00:34 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   33C    P0             49W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 730a06
Wall time: 1.0007 seconds
Process running with session ID 69812
Original token count: 0
Output:

Chunk ID: dc49de
Wall time: 3.1347 seconds
Process exited with code 0
Original token count: 846
Output:
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break from `Tensor.item()`, consider setting:
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     torch._dynamo.config.capture_scalar_outputs = True
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] or:
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] to include these operations in the captured graph.
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] 
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break: from user code at:
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]   File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/reference.py", line 89, in forward
W0428 00:00:39.342000 1343735 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     L = int(seq_lens[b].item())
W0428 00:00:39.3

... (1988 more chars)

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: e9745a
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:00:48 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   33C    P0             49W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 9e9cbb
Wall time: 1.0011 seconds
Process running with session ID 25657
Original token count: 0
Output:

Chunk ID: 641fab
Wall time: 5.0011 seconds
Process running with session ID 25657
Original token count: 0
Output:

Chunk ID: b2a421
Wall time: 2.1852 seconds
Process exited with code 0
Original token count: 2
Output:
PASS

Chunk ID: 35a6bd
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:01:04 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   34C    P0             80W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 8537c7
Wall time: 1.0010 seconds
Process running with session ID 27593
Original token count: 0
Output:

Chunk ID: 0e28ef
Wall time: 3.4139 seconds
Process exited with code 0
Original token count: 846
Output:
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break from `Tensor.item()`, consider setting:
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     torch._dynamo.config.capture_scalar_outputs = True
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] or:
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] to include these operations in the captured graph.
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] 
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break: from user code at:
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]   File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/reference.py", line 89, in forward
W0428 00:01:08.756000 1344526 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     L = int(seq_lens[b].item())
W0428 00:01:08.7

... (1988 more chars)

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: a73b76
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:01:20 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   33C    P5             45W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 782111
Wall time: 1.0010 seconds
Process running with session ID 7512
Original token count: 0
Output:

Chunk ID: b144f9
Wall time: 5.0011 seconds
Process running with session ID 7512
Original token count: 0
Output:

Chunk ID: df3b0b
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 2
Output:
PASS

Chunk ID: 151fb4
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:01:35 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   34C    P0             63W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 15d43f
Wall time: 1.0005 seconds
Process running with session ID 96235
Original token count: 0
Output:

Chunk ID: 3fa53c
Wall time: 3.3095 seconds
Process exited with code 0
Original token count: 846
Output:
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break from `Tensor.item()`, consider setting:
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     torch._dynamo.config.capture_scalar_outputs = True
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] or:
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] to include these operations in the captured graph.
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] 
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break: from user code at:
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]   File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/reference.py", line 89, in forward
W0428 00:01:39.425000 1344764 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     L = int(seq_lens[b].item())
W0428 00:01:39.4

... (1988 more chars)

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: 024eba
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 1521
Output:
import math

import torch
import torch.nn as nn
import triton
import triton.language as tl


OP_TYPE = "attention"
SUPPORTED_PRECISIONS = ["bf16"]
HARDWARE_REQUIRED = ["RTX_PRO_6000", "H100", "B200"]


@triton.jit
def _paged_attn_decode_kernel(
    query,
    kv_cache,
    block_table,
    seq_lens,
    out,
    NUM_HEADS: tl.constexpr,
    NUM_KV_HEADS: tl.constexpr,
    HEAD_DIM: tl.constexpr,
    PAGE_SIZE: tl.constexpr,
    NUM_PAGES: tl.constexpr,
    GROUP_SIZE: tl.constexpr,
    SCALE: tl.constexpr,
):
    b = tl.program_id(0)
    h = tl.program_id(1)
    kv_h = h // GROUP_SIZE

    offs_d = tl.arange(0, HEAD_DIM)
    offs_t = tl.arange(0, PAGE_SIZE)

    q = tl.load(query + (b * NUM_HEADS + h) * HEAD_DIM + offs_d).to(tl.float32)
    seqlen = tl.load(seq_lens + b)

    m = tl.full((), -float("inf"), tl.float32)
    l = tl.full((), 0.0, tl.float32)
    acc = tl.zeros((HEAD_DIM,), tl.float32)

    for page_idx in range(0, NUM_PAGES):
        block_id = tl.load(block_table + b * NUM_PAGES + page_idx)
        token_idx = page_idx * PAGE_SIZE + offs_t
        valid_t = token_idx < seqlen

        base = (
            ((block_id * PAGE_SIZE + offs_t[:, None]) * NUM_KV_HEADS + kv_h)
            * (HEAD_DIM * 2)
            + offs_d[None, :]
        )
        mask = valid_t[:, None]
        k = tl.load(kv_cache + base, mask=mask, other=0.0).to(tl.float32)
        v = tl.loa

... (4687 more chars)

output:
  Success. Updated the following files:
  M /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/solution.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

output:
  Success. Updated the following files:
  D /home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/dot_test.py
metadata:
  exit_code: 0
  duration_seconds: 0.0

Chunk ID: 57936c
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 1245
Output:
import math

import torch
import torch.nn as nn
import triton
import triton.language as tl


OP_TYPE = "attention"
SUPPORTED_PRECISIONS = ["bf16"]
HARDWARE_REQUIRED = ["RTX_PRO_6000", "H100", "B200"]

BATCH = 8
NUM_HEADS = 32
NUM_KV_HEADS = 8
HEAD_DIM = 128
SEQ_LEN = 1024
PAGE_SIZE = 16


@triton.jit
def _paged_attn_decode_grouped_kernel(
    query,
    kv_cache,
    block_table,
    seq_lens,
    out,
    NUM_HEADS: tl.constexpr,
    NUM_KV_HEADS: tl.constexpr,
    HEAD_DIM: tl.constexpr,
    PAGE_SIZE: tl.constexpr,
    NUM_PAGES: tl.constexpr,
    GROUP_SIZE: tl.constexpr,
    BLOCK_N: tl.constexpr,
    PAGES_PER_TILE: tl.constexpr,
    SCALE: tl.constexpr,
):
    b = tl.program_id(0)
    kv_h = tl.program_id(1)

    offs_g = tl.arange(0, GROUP_SIZE)
    offs_d = tl.arange(0, HEAD_DIM)
    offs_n = tl.arange(0, BLOCK_N)
    q_heads = kv_h * GROUP_SIZE + offs_g

    q = tl.load(
        query + (b * NUM_HEADS + q_heads[:, None]) * HEAD_DIM + offs_d[None, :]
    )
    seqlen = tl.load(seq_lens + b)

    m = tl.full((GROUP_SIZE,), -float("inf"), tl.float32)
    l = tl.zeros((GROUP_SIZE,), tl.float32)
    acc = tl.zeros((GROUP_SIZE, HEAD_DIM), tl.float32)

    for page_base in range(0, NUM_PAGES, PAGES_PER_TILE):
        page_ids = page_base + offs_n // PAGE_SIZE
        page_offs = offs_n % PAGE_SIZE
        token_idx = page_ids * PAGE_SIZE + page_offs
        valid_n = (p

... (3583 more chars)

Chunk ID: 822477
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:02:32 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   32C    P8             11W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: 867560
Wall time: 1.0011 seconds
Process running with session ID 86896
Original token count: 0
Output:

Chunk ID: e84c5c
Wall time: 5.0010 seconds
Process running with session ID 86896
Original token count: 0
Output:

Chunk ID: 9d1f15
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 2
Output:
PASS

Chunk ID: 8e5f45
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 5
Output:
All checks passed!

Chunk ID: b82fb6
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:02:57 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   32C    P3             44W /  600W |     508MiB /  97887MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: b273b2
Wall time: 0.0000 seconds
Process exited with code 5
Original token count: 85
Output:
============================= test session starts ==============================
platform linux -- Python 3.11.15, pytest-9.0.3, pluggy-1.6.0
rootdir: /home/infatoshi/cuda/KernelBench-Hard
configfile: pyproject.toml
plugins: anyio-4.13.0
collected 0 items

============================ no tests ran in 0.00s =============================

Chunk ID: fc20b6
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 29
Output:
/home/infatoshi/cuda/KernelBench-Hard/tests/test_eval.py
/home/infatoshi/cuda/KernelBench-Hard/tests/__init__.py

Chunk ID: 54d1de
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 166
Output:
[project]
name = "kernelbench-hard"
version = "0.1.0"
description = "Surgical GPU kernel benchmark. Small deck, frontier agents, roofline metric, link-don't-spoil problem briefs."
requires-python = ">=3.11"
dependencies = [
    "torch>=2.11",
    "numpy>=1.26",
    "pyyaml>=6.0",
    "rich>=13.7",
    "matplotlib>=3.9",
    "pytest>=8.0",
    "ruff>=0.6",
    "einops>=0.8.2",
    "requests<2.33",
]

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[tool.hatch.build.targets.wheel]
packages = ["src"]

[tool.ruff]
line-length = 100
target-version = "py311"

[tool.ruff.lint]
select = ["E", "F", "W", "I", "B", "UP"]
ignore = ["E501"]

Chunk ID: 6b44f2
Wall time: 1.0011 seconds
Process running with session ID 25673
Original token count: 0
Output:

Chunk ID: 2f1caa
Wall time: 0.0000 seconds
Process exited with code 2
Original token count: 779
Output:
============================= test session starts ==============================
platform linux -- Python 3.11.15, pytest-9.0.3, pluggy-1.6.0
rootdir: /home/infatoshi/cuda/KernelBench-Hard
configfile: pyproject.toml
plugins: anyio-4.13.0
collected 11 items / 3 errors

==================================== ERRORS ====================================
_ ERROR collecting outputs/runs/20260427_131223_opencode_openrouter-pinned_minimax_minimax-m2.7_06_sonic_moe_swiglu/scratch/test_triton.py _
ImportError while importing test module '/home/infatoshi/cuda/KernelBench-Hard/outputs/runs/20260427_131223_opencode_openrouter-pinned_minimax_minimax-m2.7_06_sonic_moe_swiglu/scratch/test_triton.py'.
Hint: make sure your test modules/packages have valid Python names.
Traceback:
../../.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/importlib/__init__.py:126: in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
outputs/runs/20260427_131223_opencode_openrouter-pinned_minimax_minimax-m2.7_06_sonic_moe_swiglu/scratch/test_triton.py:5: in <module>
    import solution
E   ModuleNotFoundError: No module named 'solution'
_ ERROR collecting outputs/runs/20260427_184750_opencode_openrouter-pinned_qwen_qwen3.6-27b_03_paged_attention/scratch/test_triton.py _
outputs/runs/20260427_184750_open

... (1719 more chars)

Chunk ID: c561fc
Wall time: 0.7502 seconds
Process exited with code 0
Original token count: 105
Output:
============================= test session starts ==============================
platform linux -- Python 3.11.15, pytest-9.0.3, pluggy-1.6.0
rootdir: /home/infatoshi/cuda/KernelBench-Hard
configfile: pyproject.toml
plugins: anyio-4.13.0
collected 10 items

tests/test_eval.py ..........                                            [100%]

============================== 10 passed in 0.52s ==============================

Chunk ID: 7af7d5
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 492
Output:
Tue Apr 28 00:03:30 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 595.58.03              Driver Version: 595.58.03      CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    On  |   00000000:01:00.0  On |                  Off |
| 30%   32C    P8             17W /  600W |     508MiB /  97887MiB |      3%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                           

... (569 more chars)

Chunk ID: e5b11d
Wall time: 1.0009 seconds
Process running with session ID 35010
Original token count: 0
Output:

Chunk ID: f8d4ca
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 846
Output:
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break from `Tensor.item()`, consider setting:
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     torch._dynamo.config.capture_scalar_outputs = True
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] or:
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] to include these operations in the captured graph.
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] 
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0] Graph break: from user code at:
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]   File "/home/infatoshi/cuda/KernelBench-Hard/problems/03_paged_attention/reference.py", line 89, in forward
W0428 00:03:34.156000 1345498 .venv/lib/python3.11/site-packages/torch/_dynamo/variables/tensor.py:1379] [0/0]     L = int(seq_lens[b].item())
W0428 00:03:34.1

... (1988 more chars)

Chunk ID: 5a51bc
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 0
Output:

Chunk ID: 765ab9
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 0
Output:

Chunk ID: 7b973d
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 29
Output:
PROMPT.txt
__pycache__
benchmark.py
check.py
framework.txt
problem.yaml
reference.py
shapes.py
solution.py
sota.py

Chunk ID: fab2bb
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 2
Output:
triton