high performance computing on graphics processing units: hgpu.org

Yinan Li, Bailu Ding, Ziyun Wei, Lukas Maas, Momin Al-Ghosien, Spyros Blanas, Nicolas Bruno, Carlo Curino, Matteo Interlandi, Craig Peeper, Kaushik Rajan, Surajit Chaudhuri, Johannes Gehrke

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Tags: Benchmarking, Computer science, Databases, Memory, nVidia, nVidia A100, nVidia H100

August 31, 2025 by hgpu

Inter-APU Communication on AMD MI300A Systems via Infinity Fabric: a Deep Dive

Gabin Schieffer, Jacob Wahlgren, Ruimin Shi, Edgar A. León, Roger Pearce, Maya Gokhale, Ivy Peng

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250, AMD Radeon Instinct MI300A, APU, ATI, Benchmarking, Computer science, HIP, HPC, MPI, Performance

August 24, 2025 by hgpu

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

Jianghui Wang, Vinay Joshi, Saptarshi Majumder, Xu Chao, Bin Ding, Ziqiong Liu, Pratik Prabhanjan Brahma, Dong Li, Zicheng Liu, Emad Barsoum

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Tags: AMD Radeon Instinct MI300X, ATI, Benchmarking, Code generation, Computer science, Deep learning, Package, Python, ROCm, Triton

August 3, 2025 by hgpu

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Juan José Ropero, Manuel de Castro, Diego R. Llanos

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Tags: AMD FirePro W7800, ATI, Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia RTX 4500 Ada, OpenCL, Package

August 3, 2025 by hgpu

Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks

Aaron Jarmusch, Nathan Graddon, Sunita Chandrasekaran

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Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, nVidia GeForce RTX 5080, nVidia H100, Performance, PTX

July 20, 2025 by hgpu

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

Joshua H. Davis, Daniel Nichols, Ishan Khillan, Abhinav Bhatele

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Tags: Benchmarking, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, OpenMP, Package

July 6, 2025 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

Towards Calculating HPC CUDA Kernel Performance on Nvidia GPUs

An HPC Benchmark Survey and Taxonomy for Characterization

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

AnnotationGym: A Generic Framework for Automatic Source Code Annotation

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

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Scaling GPU-Accelerated Databases beyond GPU Memory Size

Inter-APU Communication on AMD MI300A Systems via Infinity Fabric: a Deep Dive

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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