high performance computing on graphics processing units: hgpu.org

Ming Li, Ziqian Bi, Tianyang Wang, Yizhu Wen, Qian Niu, Junyu Liu, Benji Peng, Sen Zhang, Xuanhe Pan, Jiawei Xu, Jinlang Wang, Keyu Chen, Caitlyn Heqi Yin, Pohsun Feng, Ming Liu

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Tags: Book, Computer science, CUDA, Deep learning, FPGA, Machine learning, nVidia, OpenCL, OpenGL, TPU, Vulkan

October 13, 2024 by hgpu

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Dennis Liew, Tiago Cogumbreiro, Julien Lange

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, Package, Performance

October 13, 2024 by hgpu

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

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

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

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 & Test Pipeline of Code Repositories on ANY Language and ANY Platform

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

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Jailbreaking LLM-Controlled Robots

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

General-Purpose Computing on Tensor Processors

Testing GPU Numerics: Finding Numerical Differences Between NVIDIA and AMD GPUs

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Efficient Configuration of Heterogeneous Resources and Task Scheduling Strategies in Deep Learning Auto-Tuning Systems

Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Deep Learning and Machine Learning with GPGPU and CUDA: Unlocking the Power of Parallel Computing

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Recent source codes

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

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

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

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

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

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