high performance computing on graphics processing units: hgpu.org

Programming

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Inferring the Scheduling Policies of an Embedded CUDA GPU

Nathan Otterness, Ming Yang, Tanya Amert, James H. Anderson, F. Donelson Smith

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Tegra TX1, Package, Task scheduling

May 22, 2017 by hgpu

Design of Hardware Accelerator for Lempel-Ziv 4 (LZ4) Compression

Sang Muk Lee, Ji Hoon Jang, Jung Hwan Oh, Ji Kwang Kim, Seung Eun Lee

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Tags: Algorithms, Compression, Computer science, FPGA

May 22, 2017 by hgpu

CLBlast: A Tuned OpenCL BLAS Library

Cedric Nugteren

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Tags: AMD Radeon R9 M370X, ARM, ATI, BLAS, Computer science, Intel HD 5100, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan X, OpenCL, Package

May 18, 2017 by hgpu

Fast GPU-Based Seismogram Simulation from Microseismic Events in Marine Environments Using Heterogeneous Velocity Models

Saptarshi Das, Xi Chen, Michael P. Hobson

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Tags: CUDA, Differential equations, Earth and Space Sciences, Geophysics, Heterogeneous systems, nVidia, Partial differential equations, PDEs, Seismology, Spectral methods, Tesla C2075, Tesla K20, Visualization, Wave equation

May 18, 2017 by hgpu

Group Marching Tree: Sampling-Based Approximately Optimal Motion Planning on GPUs

Brian Ichter, Edward Schmerling, Marco Pavone

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 980, nVidia Tegra TX1, Robotics

May 18, 2017 by hgpu

Efficient Parallel Methods for Deep Reinforcement Learning

Alfredo V. Clemente, Humberto N. Castejon, Arjun Chandra

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Tags: Algorithms, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GXT 980 Ti, Package, Python, TensorFlow

May 18, 2017 by hgpu

Real-Time Adaptive Image Compression

Oren Rippel, Lubomir Bourdev

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Tags: Algorithms, Compression, Computer science, Computer vision, Machine learning, nVidia, nVidia GeForce GTX 980 Ti

May 18, 2017 by hgpu

Accelerating solutions of PDEs with GPU-based swept time-space decomposition

Daniel J Magee, Kyle E Niemeyer

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Tags: Algorithms, cfd, Computational Physics, CUDA, Differential equations, Fluid dynamics, nVidia, Package, Partial differential equations, PDEs, Physics, Tesla K40

May 11, 2017 by hgpu

Block-Parallel IDA* for GPUs

Satoru Horie, Alex Fukunaga

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GRID K520, Package

May 11, 2017 by hgpu

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

Xinyu Zhang, Srinjoy Das, Ojash Neopane, Ken Kreutz-Delgado

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Tags: Algorithms, Computer science, Computer vision, Deep learning, DSP, FPGA, Neural networks

May 11, 2017 by hgpu

Resource-Aware Just-in-Time OpenCL Compiler for Coarse-Grained FPGA Overlays

Abhishek Kumar Jain, Douglas L. Maskell, Suhaib A. Fahmy

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Tags: ARM, Computer science, DSP, FPGA, Heterogeneous systems, OpenCL

May 11, 2017 by hgpu

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Konstantinos Krommydas

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 7660, ATI Radeon HD 7970, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Performance, Tesla K20, Thesis

May 9, 2017 by hgpu

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

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Inferring the Scheduling Policies of an Embedded CUDA GPU

Design of Hardware Accelerator for Lempel-Ziv 4 (LZ4) Compression

CLBlast: A Tuned OpenCL BLAS Library

Fast GPU-Based Seismogram Simulation from Microseismic Events in Marine Environments Using Heterogeneous Velocity Models

Group Marching Tree: Sampling-Based Approximately Optimal Motion Planning on GPUs

Efficient Parallel Methods for Deep Reinforcement Learning

Real-Time Adaptive Image Compression

Accelerating solutions of PDEs with GPU-based swept time-space decomposition

Block-Parallel IDA* for GPUs

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

Resource-Aware Just-in-Time OpenCL Compiler for Coarse-Grained FPGA Overlays

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Recent source codes

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

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

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