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TrimZero: A Torch Recurrent Module for Efficient Natural Language Processing

Jin-Hwa Kim, Jeonghee Kim, Jung-Woo Ha, Byoung-Tak Zhang

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Tags: Computer science, CUDA, Deep learning, Lua, Machine learning, Neural networks, NLP, nVidia, Package, RNN, Torch

May 3, 2016 by hgpu

Automatic Test Case Reduction for OpenCL

Moritz Pflanzer, Alastair F. Donaldson, Andrei Lascu

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia GeForce GTX Titan, OpenCL

May 3, 2016 by hgpu

Polly-ACC: Transparent compilation to heterogeneous hardware

Tobias Grosser, Torsten Hoefler

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, LLVM, nVidia, nVidia GeForce GT 730 M, nVidia GeForce GTX Titan Black

May 3, 2016 by hgpu

Exposing Errors Related to Weak Memory in GPU Applications

Tyler Sorensen, Alastair F. Donaldson

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, nVidia Quadro K5200, Tesla C2050, Tesla C2075, Tesla K20

May 3, 2016 by hgpu

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Andreas Klockner, Lucas C. Wilcox, T. Warburton

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Code generation, Computer science, Fortran, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, Prefetch, Programming Languages, Python, Tesla K40

April 29, 2016 by hgpu

On the design of sparse hybrid linear solvers for modern parallel architectures

Stojce Nakov

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, MPI, nVidia, Sparse linear iterative solvers, Sparse matrix, Tesla K40, Tesla M2070, Thesis

April 29, 2016 by hgpu

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Alcides Fonseca, Bruno Cabral, Joao Rafael, Ivo Correia

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Tags: Computer science, Java, OpenCL, Package, Programming Languages

April 29, 2016 by hgpu

Adaptive GPU Array Layout Auto-Tuning

Nicolas Weber, Michael Goesele

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Tags: Computer science, CUDA, Linear Algbera, nVidia, nVidia GeForce GTX Titan X, Package, Performance, Tesla K20

April 29, 2016 by hgpu

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

Nilothpal Talukder

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Tags: Algorithms, Computer science, CUDA, Data mining, Databases, MPI, nVidia, Tesla C2075, Thesis

April 29, 2016 by hgpu

GPU-Aware Non-contiguous Data Movement In Open MPI

Wei Wu, George Bosilca, Rolf vandeVaart, Sylvain Jeaugey, Jack Dongarra

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Tags: Computer science, CUDA, MPI, nVidia, Tesla K40

April 26, 2016 by hgpu

Investigating performance portability of a highly scalable particle-in-cell simulation code on various multi-core architectures

Benjamin Worpitz

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Tags: Computer science, CUDA, Intel Xeon Phi, OpenMP, Package, Particle-in-cell methods, Performance, performance portability, Tesla K20, Tesla K80, Thesis

April 26, 2016 by hgpu

To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures

Feng Zhang, Jidong Zhai, Wenguang Chen, Bingsheng He, Shuhao Zhang

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Tags: Benchmarking, Computer science, OpenCL, Package

April 26, 2016 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

TrimZero: A Torch Recurrent Module for Efficient Natural Language Processing

Automatic Test Case Reduction for OpenCL

Polly-ACC: Transparent compilation to heterogeneous hardware

Exposing Errors Related to Weak Memory in GPU Applications

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

On the design of sparse hybrid linear solvers for modern parallel architectures

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Adaptive GPU Array Layout Auto-Tuning

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

GPU-Aware Non-contiguous Data Movement In Open MPI

Investigating performance portability of a highly scalable particle-in-cell simulation code on various multi-core architectures

To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures

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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