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GPU-SPARC: Accelerating Parallelism in Multi-GPU Real-Time Systems

Wookhyun Han, Hwidong Bae, Hyosu Kim, Jiyoen Lee, Insik Shin

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Tags: Computer science, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Package, Performance

August 13, 2014 by hgpu

A CUDA-Based Real Parameter Optimization Benchmark

Ke Ding, Ying Tan

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 560 Ti, Optimization, Package

July 30, 2014 by hgpu

Benchmarking the Memory Hierarchy of Modern GPUs

Xinxin Mei, Kaiyong Zhao, Chengjian Liu, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Package, Performance

July 14, 2014 by hgpu

A Parallelized Implementation for H. 264 Real-time Encoding Scheme

Young Chun Kwon, Chanho Park, Daeseok Oh, WooSuk Jang, Nakhoon Baek

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Tags: H.264/AVC, Image processing, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Video encoding

July 6, 2014 by hgpu

Performance Evaluation of Parallel AES Implementations over CUDA GPU Framework

Chakchai So-In, Sarayut Poolsanguan, Chartchai Poonriboon, Kanokmon Rujirakul, Comdet Phudphut

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Tags: AES, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Security

June 27, 2014 by hgpu

Comparison of Random Number Generators in Particle Swarm Optimization Algorithm

Ke Ding, Ying Tan

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Particle swarm optimization, Pseudo-random number generators

June 22, 2014 by hgpu

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian Movement

Sankha Baran Dutta

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Tags: Ant colony optimization, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Thesis

June 5, 2014 by hgpu

Heterogeneity-aware Fault Tolerance using a Self-Organizing Runtime System

Mario Kicherer, Wolfgang Karl

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 560 Ti, Operating systems

May 17, 2014 by hgpu

Real-time Simultaneous Pose and Shape Estimation for Articulated Objects Using a Single Depth Camera

Mao Ye, Ruigang Yang

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 560 Ti

May 2, 2014 by hgpu

Computational cost estimates for parallel shared memory isogeometric multi-frontal solvers

M.Wozniak, K.Kuznik, M. Paszynski, V. M. Calo, D. Pardo

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Performance, Tesla C2070

April 21, 2014 by hgpu

Performance Analysis for GPU-based Ray-triangle Algorithms

Juan J. Jimenez, Carlos J. Ogayar, Jose M. Noguera, Felix Paulano

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Performance, Raytracing

March 6, 2014 by hgpu

Computation of Galois field expressions for quaternary logic functions on GPUs

Dusan B. Gajic

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Tags: Algorithms, ATI, ATI Radeon HD 6750, Computer science, FFT, nVidia, nVidia GeForce GTX 560 Ti, OpenCL

February 15, 2014 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU-SPARC: Accelerating Parallelism in Multi-GPU Real-Time Systems

A CUDA-Based Real Parameter Optimization Benchmark

Benchmarking the Memory Hierarchy of Modern GPUs

A Parallelized Implementation for H. 264 Real-time Encoding Scheme

Performance Evaluation of Parallel AES Implementations over CUDA GPU Framework

Comparison of Random Number Generators in Particle Swarm Optimization Algorithm

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian Movement

Heterogeneity-aware Fault Tolerance using a Self-Organizing Runtime System

Real-time Simultaneous Pose and Shape Estimation for Articulated Objects Using a Single Depth Camera

Computational cost estimates for parallel shared memory isogeometric multi-frontal solvers

Performance Analysis for GPU-based Ray-triangle Algorithms

Computation of Galois field expressions for quaternary logic functions on GPUs

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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