high performance computing on graphics processing units: hgpu.org

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ConTraPh: Contrastive Learning for Parallelization and Performance Optimization

Quazi Ishtiaque Mahmud, Ali TehraniJamsaz, Nesreen K. Ahmed, Theodore L. Willke, Ali Jannesari

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Tags: Code generation, Computer science, Heterogeneous systems, HPC, LLM, nVidia, OpenACC, OpenCL, OpenMP, Tesla V100

August 10, 2025 by hgpu

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

Antonio De Caro, Gennaro Cordasco, Federico Ficarelli, Biagio Cosenza

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Tags: Biology, Chemistry, Computer science, CUDA, MPI, nVidia, nVidia V100, oneAPI, Package

August 10, 2025 by hgpu

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

Daichi Mukunoki

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Tags: Computer science, Matrix multiplication, nVidia, nVidia GeForce RTX 5060 Ti, Package, Performance

August 10, 2025 by hgpu

NPUEval: Optimizing NPU Kernels with LLMs and Open Source Compilers

Sarunas Kalade, Graham Schelle

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Tags: Code generation, Computer science, Machine learning, Programming Languages

August 3, 2025 by hgpu

GBOTuner: Autotuning of OpenMP Parallel Codes with Bayesian Optimization and Code Representation Transfer Learning

Kimsong Lor

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Tags: Bayesian, Computer science, Fortran, Neural networks, OpenMP, Thesis

August 3, 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

Performance Portable Gradient Computations Using Source Transformation

Kim Liegeois, Brian Kelley, Eric Phipps, Sivasankaran Rajamanickam, Vassil Vassilev

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Tags: AMD Radeon Instinct MI300X, ATI, Computer science, CUDA, HIP, Kokkos, Machine learning, Mathematical Software, nVidia, nVidia H100

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

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

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Paul Cardosi, Bérenger Bramas

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Tags: Computer science, CUDA, Heterogeneous systems, HIP, nVidia, nVidia A100, nVidia P100, nVidia Quadro RTX 8000, nVidia V100, Package, Task scheduling

July 20, 2025 by hgpu

Pre-Training LLMs on a budget: A comparison of three optimizers

Joel Schlotthauer, Christian Kroos, Chris Hinze, Viktor Hangya, Luzian Hahn, Fabian Küch

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Tags: Artificial intelligence, Computer science, CUDA, LLM, Machine learning, nVidia, nVidia A100

July 20, 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

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

ConTraPh: Contrastive Learning for Parallelization and Performance Optimization

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

NPUEval: Optimizing NPU Kernels with LLMs and Open Source Compilers

GBOTuner: Autotuning of OpenMP Parallel Codes with Bayesian Optimization and Code Representation Transfer Learning

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

Performance Portable Gradient Computations Using Source Transformation

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Kevin: Multi-Turn RL for Generating CUDA Kernels

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Pre-Training LLMs on a budget: A comparison of three optimizers

Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks

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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