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Optimizing exact computation of Betweenness Centrality for CUDA

Aakriti Gupta

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Tags: Computer science, CUDA, Networks, nVidia

February 15, 2014 by hgpu

Accelerator Aware MPI Micro-benchmarking using CUDA, OpenACC and OpenCL

Sadaf Alam, Ugo Varetto

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Tags: Benchmarking, Computer science, CUDA, Intel Xeon Phi, MPI, nVidia, OpenACC, OpenCL, Performance, Tesla K20, Tesla M2090

February 15, 2014 by hgpu

Effective Multi-Modal Retrieval based on Stacked Auto-Encoders

Wei Wang, Beng Chin Ooi, Xiaoyan Yang, Dongxiang Zhang, Yueting Zhuang

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Tags: Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX Titan, Package, Python

February 14, 2014 by hgpu

High-Performance Spatial Query Processing on Big Taxi Trip Data using GPGPUs

Jianting Zhang, Simin You, Le Gruenwald

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Tags: Computer science, CUDA, Hadoop, MapReduce, Nearest neighbour, nVidia, nVidia GeForce GTX Titan

February 14, 2014 by hgpu

Porting FEASTFLOW to the Intel Xeon Phi: Lessons Learned

Ioannis E. Venetis, Georgios Goumas, Markus Geveler, Dirk Ribbrock

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Tags: Computer science, Fluid dynamics, Intel Xeon Phi, OpenCL, OpenMP, Sparse matrix

February 14, 2014 by hgpu

Multi-Kepler GPU vs. Multi-Intel MIC for spin systems simulations

M. Bernaschi, M. Bisson, F. Salvadore

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Tags: Benchmarking, Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, Physics, Spin Systems, Tesla K20

February 14, 2014 by hgpu

Multi-tier Dynamic Vectorization for Translating GPU Optimizations into CPU Performance

Hee-Seok Kim, Izzat El Hajj, John A. Stratton, Wen-Mei W. Hwu

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Tags: AMD, Computer science, nVidia, OpenCL, Performance

February 12, 2014 by hgpu

Increasing precision of uniform pseudorandom number generators

Vadim Demchik, Alexey Gulov

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Tags: Algorithms, Computer science, Extended precision, Mathematical Software, Pseudo-random number generators, Security

February 12, 2014 by hgpu

Designing Bit-Reproducible Portable High-Performance Applications

Andrea Arteaga, Oliver Fuhrer, Torsten Hoefler

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Portability, Tesla K20

February 12, 2014 by hgpu

GROMACS on Hybrid CPU-GPU and CPU-MIC Clusters: Preliminary Porting Experiences, Results and Next Steps

Sadaf Alam, Ugo Varetto

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Tags: Computer science, CUDA, GPU cluster, Hybrid computing, Intel Xeon Phi, MPI, nVidia, OpenCL, Tesla K20

February 12, 2014 by hgpu

Transparent use of Java objects on the GPU in the JaMP/OpenMP framework

Carolin Wolf

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Tags: Computer science, CUDA, Java, nVidia, OpenMP, Tesla M1060, Thesis

February 12, 2014 by hgpu

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Optimizing exact computation of Betweenness Centrality for CUDA

Accelerator Aware MPI Micro-benchmarking using CUDA, OpenACC and OpenCL

Effective Multi-Modal Retrieval based on Stacked Auto-Encoders

High-Performance Spatial Query Processing on Big Taxi Trip Data using GPGPUs

Porting FEASTFLOW to the Intel Xeon Phi: Lessons Learned

Multi-Kepler GPU vs. Multi-Intel MIC for spin systems simulations

Multi-tier Dynamic Vectorization for Translating GPU Optimizations into CPU Performance

Increasing precision of uniform pseudorandom number generators

Designing Bit-Reproducible Portable High-Performance Applications

GROMACS on Hybrid CPU-GPU and CPU-MIC Clusters: Preliminary Porting Experiences, Results and Next Steps

Transparent use of Java objects on the GPU in the JaMP/OpenMP framework

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Recent source codes

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

SW#SYCL

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

HiRep

Gaia AVU-GSR

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

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