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AMD MI355X performance boosted over 2x by kernel optimizations · 3 sources tracked

By PulseAugur Editorial · [3 sources] ·

The GPUMODE Readonflow Team, through an AMD kernel hackathon, has significantly improved end-to-end performance for the MI355X by over 2x. These optimizations, focusing on W4A4 MoE kernels, Top-K kernels, and tensor-parallel all-reduce kernels, have been integrated into AMD's AITER kernel library and the ATOM inference engine. The team aims to upstream these improvements to vLLM to achieve performance parity with CUDA vLLM, fostering community experience with ROCm stack optimization. AI

IMPACT These kernel optimizations could significantly improve inference speeds on AMD hardware, potentially closing the performance gap with NVIDIA's CUDA stack.

RANK_REASON The cluster details specific kernel optimizations and their integration into software libraries, representing a research milestone in improving hardware performance.

Read on X — SemiAnalysis →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

AMD MI355X performance boosted over 2x by kernel optimizations · 3 sources tracked

COVERAGE [3]

  1. X — SemiAnalysis TIER_1 English(EN) · SemiAnalysis_ ·

    @GPU_MODE This work has been upstreamed to the main branch of @AIatAMD’s AITER kernel library and to the ATOM inference engine. We hope this work will also be u

    @GPU_MODE This work has been upstreamed to the main branch of @AIatAMD’s AITER kernel library and to the ATOM inference engine. We hope this work will also be upstreamed to vLLM so that AMD vLLM can reach performance parity with CUDA vLLM. 3/4🧵

  2. X — SemiAnalysis TIER_1 English(EN) · SemiAnalysis_ ·

    @GPU_MODE They focused on optimizing W4A4 MoE kernels, Top-K kernels, tensor-parallel all-reduce kernels, and the MLA decode metadata planner. 2/4🧵 https://t.co

    @GPU_MODE They focused on optimizing W4A4 MoE kernels, Top-K kernels, tensor-parallel all-reduce kernels, and the MLA decode metadata planner. 2/4🧵 https://t.co/SWFbh16Op0

  3. X — SemiAnalysis TIER_1 Deutsch(DE) · SemiAnalysis_ ·

    GREAT WORK BY @GPU_MODE 🚨 FOR LAUNCHING THE $1.1mil AMD KERNEL HACKATHON.

    GREAT WORK BY @GPU_MODE 🚨 FOR LAUNCHING THE $1.1mil AMD KERNEL HACKATHON. The GPUMODE Readonflow Team’s kernels improved end-to-end MI355X performance by over 2x. We explain the optimizations below. 1/4🧵 https://t.co/2n1boLQi2j

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