30493
hgpu.org » AMD Radeon Instinct MI350X

KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta

Gang Liao, Hongsen Qin, Ying Wang, Alicia Golden, Michael Kuchnik, Yavuz Yetim, Jia Jiunn Ang, Chunli Fu, Yihan He, Samuel Hsia, Zewei Jiang, Dianshi Li, Uladzimir Pashkevich, Varna Puvvada, Feng Shi, Matt Steiner, Ruichao Xiao, Nathan Yan, Xiayu Yu, Zhou Fang, Abdul Zainul-Abedin, Ketan Singh, Hongtao Yu, Wenyuan Chi, Barney Huang, Sean Zhang, Noah Weller, Zach Marine, Wyatt Cook, Carole-Jean Wu, Gaoxiang Liu
View View   Download Download (PDF)   

Tags: , , , , , , , , , , , , , ,

January 4, 2026 by hgpu

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

Ryan Swann, Muhammad Osama, Xiaohu Guo, Bryant Nelson, Lixun Zhang, Alex Brown, Yen Ong, Ali Yazdani, Sean Siddens, Ganesh Dasika, Alex Underwood
View View   Download Download (PDF)   Source codes Source codes

Tags: , , , , , , , , , ,

December 7, 2025 by hgpu

Recent source codes

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform
RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform
CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation
HIPRT: Ray Tracing using HIP

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP
MXFP4 Training Support Codebase

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs
CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation
CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CL4SE: A Context Learning Benchmark For Software Engineering Tasks
CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models
A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5
See all packages

* * *

* * *

HGPU group © 2010-2026 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: