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SynPerf: A Hybrid Analytical-ML Framework for GPU Performance Prediction

Kaixuan Zhang, Yunfan Cui, Shuhao Zhang, Chutong Ding, Shiyou Qian, Luping Wang, Jian Cao, Guangtao Xue, Cheng Huang, Guodong Yang, Liping Zhang

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia A100, nVidia A40, nVidia H100, nVidia H20, nVidia H200, nVidia H800, nVidia L20, nVidia L40, nVidia RTX 6000 Ada, Performance, Triton

January 25, 2026 by hgpu

Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation

Le Chen1, Nuo Xu, Winson Chen, Bin Lei, Pei-Hung Lin, Dunzhi Zhou, Rajeev Thakur, Caiwen Ding, Ali Jannesari, Chunhua Liao

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Tags: Code generation, Computer science, CUDA, LLM, nVidia, nVidia H200

December 21, 2025 by hgpu

Microbenchmarking NVIDIA’s Blackwell Architecture: An in-depth Architectural Analysis

Aaron Jarmusch, Sunita Chandrasekaran

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Tags: Benchmarking, Computer science, CUDA, HPC, Machine learning, nVidia, nVidia B200, nVidia H200, PTX

December 7, 2025 by hgpu

RDMA Point-to-Point Communication for LLM Systems

Nandor Licker, Kevin Hu, Vladimir Zaytsev, Lequn Chen

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Tags: Computer science, CUDA, LLM, nVidia, nVidia H200, Package, Performance, RDMA

November 9, 2025 by hgpu

Combining Performance and Productivity: Accelerating the Network Sensing Graph Challenge with GPUs and Commodity Data Science Software

Siddharth Samsi, Dan Campbell, Emanuel Scoullos, Oded Green

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Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, nVidia A100, nVidia H100, nVidia H200, Sensing

September 14, 2025 by hgpu

Harnessing Batched BLAS/LAPACK Kernels on GPUs for Parallel Solutions of Block Tridiagonal Systems

David Jin, Alexis Montoison, Sungho Shin

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Tags: AMD Radeon Instinct MI300X, ATI, Benchmarking, BLAS, Computer science, CUDA, Factorization, Julia, nVidia, nVidia H200, Package, ROCm

September 7, 2025 by hgpu

Kevin: Multi-Turn RL for Generating CUDA Kernels

Carlo Baronio, Pietro Marsella, Ben Pan, Simon Guo, Silas Alberti

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Tags: Artificial intelligence, Computer science, CUDA, LLM, Machine learning, nVidia, nVidia H100, nVidia H200, Performance

July 20, 2025 by hgpu

Serving LLMs in HPC Clusters: A Comparative Study of Qualcomm Cloud AI 100 Ultra and High-Performance GPUs

Mohammad Firas Sada, John J. Graham, Elham E Khoda, Mahidhar Tatineni, Dmitry Mishin, Rajesh K. Gupta, Rick Wagner, Larry Smarr, Thomas A. DeFanti, Frank Würthwein

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Tags: AMD Radeon Instinct MI300A, ATI, Cloud, Computer science, Deep learning, HPC, nVidia, nVidia A100, nVidia H200

July 13, 2025 by hgpu

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

Inside VOLT: Designing an Open-Source GPU Compiler (Tool)

SciDef: Automated Definition Extraction from Scientific Literature

SciDef: Automating Definition Extraction from Academic Literature with Large Language Models

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

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