Learning Exact NVIDIA SASS Encoders with F 2 Linear Algebra

arXiv:2608.20532 · cs.LG · Submitted 2026-08-20 · Read on arXiv

cs.LG

Submitted: 2026-08-20

Updated: 2026-09-28

Code: https://github.com/JiadingGai/f2asm

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Core — 4× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
• FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
• FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
• Optimizing CUDA like a Human: Micro-Profiling Tools as Expert Surrogates for LLM-Based GPU Kernel Optimization

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