high performance computing on graphics processing units: hgpu.org

hgpu.org » Software Engineering

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K. A. Hawick, D. P. Playne

View

Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

May 25, 2013 by hgpu

Implementing Continuous Integration Software in an Established Computational Chemistry Software Package

Robin M. Betz, Ross C. Walker

View

Download (PDF)

Tags: Benchmarking, Chemistry, Computational chemistry, CUDA, Molecular dynamics, nVidia, Software Engineering, Tesla M2090

May 21, 2013 by hgpu

Modeling of High Performance Programs to Support Heterogeneous Computing

Ferosh Jacob

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, OpenCL, Software Engineering, Tesla M2070, Thesis

April 9, 2013 by hgpu

GPGPU Test Suite Minimisation: Search Based Software Engineering Performance Improvement Using Graphics Cards

Shin Yoo, Mark Harman, Shmuel Ur

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 4850, Computer science, Java, OpenCL, Software Engineering

March 21, 2013 by hgpu

A GPU-Based Parallel Algorithm for Design Structure Matrix (DSM) Partition

Jing Yuxin,Huang Yu,Shikun Zhang, Cui Weilong

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, Software Engineering

December 10, 2012 by hgpu

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

Tiark Rompf

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Software Engineering, Tesla C2050, Thesis

December 8, 2012 by hgpu

Efficient Hybrid Execution of C++ Applications using Intel(R) Xeon Phi(TM) Coprocessor

Jiri Dokulil, Enes Bajrovic, Siegfried Benkner, Sabri Pllana, Martin Sandrieser, Beverly Bachmayer

View

Download (PDF)

Tags: Computer science, Intel, Intel Phi, Software Engineering

December 2, 2012 by hgpu

Medical Image Registration using OpenCL

Sachitsing Dwarkan

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 5870, ATI Radeon HD 6750 M, Image processing, Image registration, Medicine, OpenCL, Software Engineering, Thesis

May 23, 2012 by hgpu

Constructing Natural Neighbor Interpolation Based Grid DEM Using CUDA

Simin You, Jianting Zhang

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, Software Engineering

May 10, 2012 by hgpu

GPU Acceleration for the C++ Standard Template Library

Christian DeLozier

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 570, OpenCL, Package, Programming techniques, Software Engineering

May 2, 2012 by hgpu

Verifying GPU Kernels by Test Amplification

Alan Leung, Manish Gupta, Yuvraj Agarwal, Rajesh Gupta, Ranjit Jhala

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Programming Languages, Software Engineering

April 12, 2012 by hgpu

Full system simulation of many-core heterogeneous SoCs using GPU and QEMU semihosting

Shivani Raghav, Christian Pinto, Martino Ruggiero, Andrea Marongiu, David Atienza, Luca Benini

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Operating systems, Software Engineering, Tesla C2070

March 26, 2012 by hgpu

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

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

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

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

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

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

Implementing Continuous Integration Software in an Established Computational Chemistry Software Package

Modeling of High Performance Programs to Support Heterogeneous Computing

GPGPU Test Suite Minimisation: Search Based Software Engineering Performance Improvement Using Graphics Cards

A GPU-Based Parallel Algorithm for Design Structure Matrix (DSM) Partition

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

Efficient Hybrid Execution of C++ Applications using Intel(R) Xeon Phi(TM) Coprocessor

Medical Image Registration using OpenCL

Constructing Natural Neighbor Interpolation Based Grid DEM Using CUDA

GPU Acceleration for the C++ Standard Template Library

Verifying GPU Kernels by Test Amplification

Full system simulation of many-core heterogeneous SoCs using GPU and QEMU semihosting

Recent source codes

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

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

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

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

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

Most viewed papers (last 30 days)