high performance computing on graphics processing units: hgpu.org

Yunjae Lee, Juntaek Lim, Jehyeon Bang, Eunyeong Cho, Huijong Jeong, Taesu Kim, Hyungjun Kim, Joonhyung Lee, Jinseop Im, Ranggi Hwang, Se Jung Kwon, Dongsoo Lee, Minsoo Rhu

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Tags: AI, Benchmarking, Computer science, CUDA, Intel, Intel Gaudi-2, nVidia, nVidia A100, Performance

January 6, 2025 by hgpu

Performant Automatic BLAS Offloading on Unified Memory Architecture with OpenMP First-Touch Style Data Movement

Junjie Li

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Tags: Computer science, CUDA, HPC, Linear Algebra, nVidia, nVidia GH200, OpenMPI, Physics, Quantum Physics

January 6, 2025 by hgpu

A comparison of HPC-based quantum computing simulators using Quantum Volume

Lourens van Niekerk, Dhiraj Kumar, Aasish Kumar Sharma, Tino Meisel, Martin Leandro Paleico, Christian Boehme

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Tags: Benchmarking, CUDA, nVidia, nVidia A100, OpenCL, Overview, Physics, Quantum computing, Review

January 6, 2025 by hgpu

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Avinash Maurya

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Tags: AI, Artificial intelligence, Computer science, CUDA, Deep learning, HPC, nVidia, nVidia DGX-A100, Package, Thesis

December 29, 2024 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

Debunking the CUDA Myth Towards GPU-based AI Systems

Performant Automatic BLAS Offloading on Unified Memory Architecture with OpenMP First-Touch Style Data Movement

A comparison of HPC-based quantum computing simulators using Quantum Volume

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Recent source codes

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

Device Virtual Machine (DVM)

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

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