high performance computing on graphics processing units: hgpu.org

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Four styles of parallel and net programming

Zhiwei Xu, Yongqiang He, Wei Lin, Li Zha

Tags: Computer science, CUDA, MapReduce, nVidia, Programming techniques

January 8, 2011 by hgpu

Quick-CULLIDE: fast inter- and intra-object collision culling using graphics hardware

Naga K. Govindaraju, Ming C. Lin, Dinesh Manocha

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Tags: 3D Graphics and Realism, Collision detection, Computer science, nVidia, nVidia GeForce FX 6800 Ultra, OpenGL

January 8, 2011 by hgpu

Improving energy and power efficiency using NComputing and approaches for predicting reliability of complex computing systems

Hoang Pham, Hoang Pham

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Tags: Computer science, Energy-efficient computing, nVidia, nVidia GeForce 9800 GX2

January 8, 2011 by hgpu

Parallel algorithms to a parallel hardware: Designing vision algorithms for a GPU

Jun-Sik Kim, Myung Hwangbo, Takeo Kanade

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GTX, Optical flow

January 8, 2011 by hgpu

ClearPath: highly parallel collision avoidance for multi-agent simulation

Stephen J. Guy, Jatin Chhugani, Changkyu Kim, Nadathur Satish, Ming Lin, Dinesh Manocha, Pradeep Dubey

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Tags: Artificial intelligence, Computer science, Larrabee, Optimization

January 8, 2011 by hgpu

Self-Configuring Applications for Heterogeneous Systems: Program Composition and Optimization Using Cognitive Techniques

M. W. Hall, Y. Gil, R. F. Lucas

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Tags: Compilers, Computer science, FPGA, nVidia, Optimization, Performance

January 8, 2011 by hgpu

Metaprogramming GPUs with Sh

Michael McCool, Stefanus Du Toit

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Tags: ATI, Book, Computer science, High-level Languages, nVidia, Sh

January 8, 2011 by hgpu

Combining computer vision and physics simulations using GPGPU

Justin Hensley, John Isidoro, Arcot J. Preetham

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Tags: ATI, Computer science, Computer vision

January 7, 2011 by hgpu

Thousand core chips: a technology perspective

Shekhar Borkar

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Tags: Architecture, Computer science, Review

January 7, 2011 by hgpu

A Unified Runtime System for Heterogeneous Multi-core Architectures

Cedric Augonnet, Raymond Namyst

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia Quadro FX 4600

January 7, 2011 by hgpu

JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA

Yonghong Yan, Max Grossman, Vivek Sarkar

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Source codes

Tags: Computer science, CUDA, Java, nVidia, Package, Tesla C1060

January 7, 2011 by hgpu

Power Consumption of GPUs from a Software Perspective

Sylvain Collange, David Defour, Arnaud Tisserand

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 9800 GX2, Tesla C870, Tesla D870, Tesla T10P

January 7, 2011 by hgpu

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

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

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

See all packages

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high performance computing on graphics processing units: hgpu.org

Four styles of parallel and net programming

Quick-CULLIDE: fast inter- and intra-object collision culling using graphics hardware

Improving energy and power efficiency using NComputing and approaches for predicting reliability of complex computing systems

Parallel algorithms to a parallel hardware: Designing vision algorithms for a GPU

ClearPath: highly parallel collision avoidance for multi-agent simulation

Self-Configuring Applications for Heterogeneous Systems: Program Composition and Optimization Using Cognitive Techniques

Metaprogramming GPUs with Sh

Combining computer vision and physics simulations using GPGPU

Thousand core chips: a technology perspective

A Unified Runtime System for Heterogeneous Multi-core Architectures

JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA

Power Consumption of GPUs from a Software Perspective

Recent source codes

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

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