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Equalizer 2.0 – Convergence of a Parallel Rendering Framework

Stefan Eilemann, David Steiner, Renato Pajarola

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Tags: Algorithms, Computer science, Graphics, nVidia, nVidia GeForce GTX 970, OpenGL, Package, Rendering, Virtual reality, Visualization

March 3, 2018 by hgpu

Evaluating High-Level Synthesis Techniques for Scalable Hardware-Accelerated Computing

Alfonso Rodriguez, Cesar Castanares, Teresa Riesgo, Eduardo de la Torre

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Tags: ARM, Computer science, FPGA, nVidia, nVidia GeForce GTX Titan X, OpenCL

February 17, 2018 by hgpu

Long-time Simulations with Complex Code Using Multiple Nodes of Intel Xeon Phi Knights Landing

Jonathan S. Graf, Matthias K. Gobbert, Samuel Khuvis

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Tags: Computer science, Differential equations, Intel Xeon Phi, MPI, OpenMP, Partial differential equations, PDEs

February 17, 2018 by hgpu

The performances of R GPU implementations of the GMRES method

Bogdan Oancea, Richard Pospisil

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 840 M, OpenCL, Performance, R

February 17, 2018 by hgpu

Input-Aware Auto-Tuning of Compute-Bound HPC Kernels

Philippe Tillet, David Cox

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Tags: Auto-Tuning, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 980 Ti, OpenCL, Package, Performance, PTX, Tesla P100

February 17, 2018 by hgpu

Transforming and Optimizing Irregular Applications for Parallel Architectures

Jing Zhang

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K20, Thesis

February 17, 2018 by hgpu

A Survey of Techniques for Improving Security of Non-volatile Memories

Sparsh Mittal, Ahmed Alsalibi

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Tags: Computer science, Hardware security, non-volatile memory, Security, survey

February 15, 2018 by sparsh0mittal

Accelerating Interpreted Programming Languages on GPUs with Just-In-Time Compilation and Runtime Optimisations

Juan Jose Fumero Alfonso

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Tags: AMD Radeon R9 295X2, ATI, Computer science, Java, nVidia, nVidia GeForce GTX Titan Black, OpenCL, R, Thesis

February 15, 2018 by hgpu

TVM: End-to-End Optimization Stack for Deep Learning

Tianqi Chen, Thierry Moreau, Ziheng Jiang, Haichen Shen, Eddie Yan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, FPGA, Machine learning, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, performance portability, TensorFlow, Tesla K80

February 15, 2018 by hgpu

Improving Locality of Unstructured Mesh Algorithms on GPUs

Andras Attila Sulyok, Gabor Daniel Balogh, Istvan Zoltan Reguly, Gihan R. Mudalige

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Tags: Algorithms, Computer science, CUDA, Finite element method, Mathematical Software, nVidia, Performance, Tesla P100

February 15, 2018 by hgpu

GPU Accelerated Finite Element Assembly with Runtime Compilation

Tao Cui, Xiaohu Guo, Hui Liu

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Tags: Computer science, CUDA, Differential equations, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Partial differential equations, PDEs, Symbolic Computation, Tesla K20, Tesla M2090, Tesla V100

February 15, 2018 by hgpu

Using Meta-heuristics and Machine Learning for Software Optimization of Parallel Computing Systems: A Systematic Literature Review

Suejb Memeti, Sabri Pllana, Alecio Binotto, Joanna Kolodziej, and Ivona Brandic

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Tags: Computer science, Machine learning, Metaheuristics, parallel computing, software optimization

February 10, 2018 by suejb.memeti

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

Equalizer 2.0 – Convergence of a Parallel Rendering Framework

Evaluating High-Level Synthesis Techniques for Scalable Hardware-Accelerated Computing

Long-time Simulations with Complex Code Using Multiple Nodes of Intel Xeon Phi Knights Landing

The performances of R GPU implementations of the GMRES method

Input-Aware Auto-Tuning of Compute-Bound HPC Kernels

Transforming and Optimizing Irregular Applications for Parallel Architectures

A Survey of Techniques for Improving Security of Non-volatile Memories

Accelerating Interpreted Programming Languages on GPUs with Just-In-Time Compilation and Runtime Optimisations

TVM: End-to-End Optimization Stack for Deep Learning

Improving Locality of Unstructured Mesh Algorithms on GPUs

GPU Accelerated Finite Element Assembly with Runtime Compilation

Using Meta-heuristics and Machine Learning for Software Optimization of Parallel Computing Systems: A Systematic Literature Review

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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