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New F2Asm Tool Learns Exact SASS Encoders for NVIDIA GPUs

By PulseAugur Editorial · [1 sources] ·

Researchers have developed F2Asm, a novel system capable of learning exact SASS encoders for NVIDIA data-center GPUs. This tool enables controlled machine-code rewriting by functioning as an open-source assembler for recent NVIDIA architectures, including Rubin SM107. F2Asm utilizes Gaussian elimination over F2 to construct encoders as vector-valued affine maps, supporting architectures like Hopper SM90/SM90a and Blackwell SM100. The system was trained on a substantial dataset of CUBINs from production libraries and CUDA archives, demonstrating exact reassembly in round-trip tests. AI

RANK_REASON Academic paper detailing a new method for learning SASS encoders. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New F2Asm Tool Learns Exact SASS Encoders for NVIDIA GPUs

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Academic paper detailing a new method for learning SASS encoders. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jiading Gai ·

    Learning Exact NVIDIA SASS Encoders with $\mathbb{F}_2$ Linear Algebra

    arXiv:2608.20532v1 Announce Type: new Abstract: NVIDIA provides a SASS disassembler but no public SASS assembler for recent data-center GPUs, limiting controlled machine-code rewriting. We present F2Asm, which learns exact 128-bit SASS encoders from paired disassembly and origina…

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