name: 04_kahan_softmax
display_name: "Kahan-corrected Softmax"
precision: fp32
regime: memory  # softmax is bandwidth-bound: 2 passes over the input tensor

# Softmax FLOPs: per-element exp + 2 reductions + divide. Roughly 5 flops/elt.
flops_formula: "5 * batch * vocab"

# Bytes moved: read x once, write y once. Both fp32.
bytes_formula: "batch * vocab * 4 + batch * vocab * 4"

hardware: [RTX_PRO_6000]
peak_tflops_key: fp32
peak_bandwidth_key: dram

# TIGHTER than default (fp32 default is 1e-4). This problem exists
# specifically to test whether the agent uses compensated summation, so
# we squeeze the tolerance to 1e-5 — naive fp16 sum across 256K elements
# drifts past this; fp32 accumulation passes; Kahan/fp32 always passes.
tolerance:
  "torch.float32": {"atol": 1.0e-5, "rtol": 1.0e-5}

# Forbidden ops — block the obvious "just call the library" cheats. The
# agent must implement softmax themselves with explicit (compensated)
# summation logic.
forbidden:
  - "torch.nn.functional.softmax"
  - "torch.softmax"
  - "F.softmax"
  - "liger_kernel.softmax"
  - "liger_kernel.transformers.softmax"
  - ".softmax("

sota:
  name: "Liger-Kernel Softmax (Triton)"
  url: "https://github.com/linkedin/Liger-Kernel"
  function: "liger_kernel.ops.softmax.LigerSoftmaxFunction"
  deps:
    - "liger-kernel>=0.5.0"
  reference_throughput_gbps_h100: 2800

num_correct_trials: 3
num_perf_trials: 30