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hgpu.org » Applications » Computer science

Exposing non-standard architectures to embedded software using compile-time virtualisation

Ian Gray, Neil C. Audsley

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Tags: Computer science, FPGA, Performance, Programming Languages, Virtualization

August 28, 2011 by hgpu

The impact of diverse memory architectures on multicore consumer software: an industrial perspective from the video games domain

George Russel, Colin Riley, Neil Henning, Uwe Dolinsky, Andrew Richards, Alastair F. Donaldson, Alexander S. van Amesfoort

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Tags: Cell processor, Computer science, Memory, Performance, Programming techniques

August 28, 2011 by hgpu

A new multi-core pipelined architecture for executing sequential programs for parallel geospatial computing

Duoduo Liao, Simon Y. Berkovich

Tags: Computer science, Programming techniques

August 28, 2011 by hgpu

Automating GPU computing in MATLAB

Chun-Yu Shei, Pushkar Ratnalikar, Arun Chauhan

Tags: Compilers, Computer science, Heterogeneous systems, Performance

August 28, 2011 by hgpu

CUDA accelerated iris template matching on Graphics Processing Units (GPUs)

N.A. Vandal, M. Savvides

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Tags: Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia GeForce GTX 470, Security

August 28, 2011 by hgpu

Real-time task reconfiguration support applied to an UAV-based surveillance system

Alecio Pedro Delazari Binotto, Edison Pignaton de Freitas, Carlos Eduardo Pereira, Andre Stork, Tony Larsson

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce 8800 GT

August 28, 2011 by hgpu

Collaborative execution environment for heterogeneous parallel systems

Aleksandar Ilic, Leonel Sousa

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Tags: Computer science, CUBLAS, CUDA, Data parallelism, FFT, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Presentation

August 28, 2011 by hgpu

Global Illumination for Advanced Computer Graphics

M. Robart, S. Hill, E. Tanguy

Tags: 3D Graphics and Realism, Algorithms, Computer science, Overview, Rasterization, Raytracing, Rendering

August 28, 2011 by hgpu

Switching to High Gear: Opportunities for Grand-Scale Real-Time Parallel Simulations

Kalyan S. Perumalla

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Review

August 27, 2011 by hgpu

directCell: hybrid systems with tightly coupled accelerators

H. Penner, U. Bacher, J. Kunigk, C. Rund, H. J. Schick

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Tags: Cell processor, Computer science, Hybrid computing, Performance

August 27, 2011 by hgpu

A breadth-first course in multicore and manycore programming

Suzanne Rivoire

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Tags: Computer science, CUDA, High-level Languages, nVidia, OpenMP, Programming techniques

August 27, 2011 by hgpu

A structured parallel periodic arnoldi shooting algorithm for RF-PSS analysis based on GPU platforms

Xue-Xin Liu, Hao Yu, Jacob Relles, Sheldon X.-D. Tan

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Tags: Algorithms, CAD, Computer science, CUDA, Numerical Analysis, nVidia, Performance, Tesla C1060

August 27, 2011 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

Exposing non-standard architectures to embedded software using compile-time virtualisation

The impact of diverse memory architectures on multicore consumer software: an industrial perspective from the video games domain

A new multi-core pipelined architecture for executing sequential programs for parallel geospatial computing

Automating GPU computing in MATLAB

CUDA accelerated iris template matching on Graphics Processing Units (GPUs)

Real-time task reconfiguration support applied to an UAV-based surveillance system

Collaborative execution environment for heterogeneous parallel systems

Global Illumination for Advanced Computer Graphics

Switching to High Gear: Opportunities for Grand-Scale Real-Time Parallel Simulations

directCell: hybrid systems with tightly coupled accelerators

A breadth-first course in multicore and manycore programming

A structured parallel periodic arnoldi shooting algorithm for RF-PSS analysis based on GPU platforms

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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