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PTask: Operating System Abstractions To Manage GPUs as Compute Devices

Christopher J. Rossbach, Jon Currey, Mark Silberstein, Baishakhi Ray, Emmett Witchel

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Tags: Computer science, CUDA, HLSL, nVidia, nVidia GeForce GT 230, nVidia GeForce GTX 470, nVidia GeForce GTX 580, OpenCL, Operating systems, Performance, Programming techniques

October 2, 2011 by hgpu

A Complete Descritpion of the UnPython and Jit4GPU Framework

Rahul Garg, Jose Nelson Amaral

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Tags: ATI, ATI CAL, ATI IL, ATI Radeon HD 5850, ATI Stream, Compilers, Computer science, OpenMP, Optimization, Performance, Python

October 2, 2011 by hgpu

Parallel probabilistic model checking on general purpose graphics processors

Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski, Anton Wijs

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Probabilistic model checking

October 2, 2011 by hgpu

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

Aleksandar Ilic, Leonel Sousa

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Tags: Computer science, CUDA, Data parallelism, FFT, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Signal processing

October 2, 2011 by hgpu

Parallel Computing based on GPGPU using Compute Unified Device Architecture

Lifeng Xu

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 580, OpenMP, Optimization, Thesis

October 1, 2011 by hgpu

Correctly Treating Synchronizations in Compiling Fine-Grained SPMD-Threaded Programs for CPU

Ziyu Guo, Eddy Z. Zhang, Xipeng Shen

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia

October 1, 2011 by hgpu

Optimizing a Semantic Comparator using CUDA-enabled Graphics Hardware

Aalap Tripathy, Suneil Mohan, Rabi Mahapatra

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Tags: Bloom filter, Computer science, CUDA, Green, Hashing, nVidia, Semantic indexing, Tesla C870

October 1, 2011 by hgpu

Customizable Domain-Specific Computing

Jason Cong, Glenn Reinman, Alex Bui, Vivek Sarkar

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Tags: Computer science, FPGA, nVidia, Performance, Programming techniques, Tesla C1060

October 1, 2011 by hgpu

CheCL: Transparent Checkpointing and Process Migration of OpenCL Applications

Hiroyuki Takizawa, Kentaro Koyama, Katuto Sato, Kazuhiko Komatsu, Hiroaki Kobayashi

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Tags: ATI, ATI Radeon HD 5870, Code generation, Compilers, Computer science, MPI, nVidia, OpenCL, Tesla C1060

October 1, 2011 by hgpu

A Comprehensive Performance Comparison of CUDA and OpenCL

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Cell processor, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Optimization, Performance

October 1, 2011 by hgpu

Accelerating Vector Calculations on GPU

Karol Grondzak, Penka Martincova, Ondrej Such

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Tesla C1060, Tutorial

October 1, 2011 by hgpu

Large Scale DNA Sequence Alignment and Kernel Method Implemented with GPUs

Songwen Pei, Wenhao Wang, Gang Wei, Baifeng Wu

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Tags: Algorithms, ATI, ATI Radeon HD 4870, Bioinformatics, Biology, Brook, Sequence alignment

October 1, 2011 by hgpu

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

PTask: Operating System Abstractions To Manage GPUs as Compute Devices

A Complete Descritpion of the UnPython and Jit4GPU Framework

Parallel probabilistic model checking on general purpose graphics processors

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

Parallel Computing based on GPGPU using Compute Unified Device Architecture

Correctly Treating Synchronizations in Compiling Fine-Grained SPMD-Threaded Programs for CPU

Optimizing a Semantic Comparator using CUDA-enabled Graphics Hardware

Customizable Domain-Specific Computing

CheCL: Transparent Checkpointing and Process Migration of OpenCL Applications

A Comprehensive Performance Comparison of CUDA and OpenCL

Accelerating Vector Calculations on GPU

Large Scale DNA Sequence Alignment and Kernel Method Implemented with GPUs

Recent source codes

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

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

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