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An efficient scheduling scheme using estimated execution time for heterogeneous computing systems

Hong Jun Choi, Dong Oh Son, Seung Gu Kang, Jong Myon Kim, Hsien-Hsin Lee, Cheol Hong Kim

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8500 GT

February 22, 2013 by hgpu

Scheduling a Parallel Sparse Direct Solver to Multiple GPUs

Kyungjoo Kim

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Tags: Computer science, CUDA, Factorization, FEM, Finite element method, Heterogeneous systems, nVidia, Package, Sparse direct solvers, Task scheduling, Tesla M2070

February 21, 2013 by hgpu

An abstract object oriented runtime system for heterogeneous parallel architecture

Jean-Marc Gratien

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Tesla C2070, Tesla T10

February 20, 2013 by hgpu

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Shuaiwen Song, Chunyi Su, Barry Rountree, Kirk W. Cameron

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Tags: Biomolecules, Computer science, CUDA, Electrostatics, Energy-efficient computing, GPU cluster, Heterogeneous systems, Machine learning, nVidia, Tesla C2075, Tesla M2090

February 18, 2013 by hgpu

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Chris J. Newburn, Rajiv Deodhar, Serguei Dmitriev, Ravi Murty, Ravi Narayanaswamy, John Wiegert, Francisco Chinchilla, Russell McGuire

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Tags: Compilers, Computer science, Heterogeneous systems, Intel, Intel Phi, Programming techniques

February 18, 2013 by hgpu

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

Sidi Ahmed Mahmoudi, Pierre Manneback

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 280, Pattern recognition, Tesla C1060

February 14, 2013 by hgpu

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

Stephen Won

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Tags: Computer vision, CUDA, Data mining, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, SIFT, Signal processing, Thesis

February 12, 2013 by hgpu

Adaptation of the MapReduce programming framework to compute-intensive data-analytics kernels

Reza Farivar

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce GTX 275, Thesis

February 9, 2013 by hgpu

Distributed multi-node, multi-GPU, heterogeneous system for 3D image reconstruction in Electrical Capacitance Tomography – network performance and application analysis

Pawel Kapusta, Michal Majchrowicz, Dominik Sankowski, Lidia Jackowska-Strumillo, Robert Banasiak

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Tags: ATI, ATI Radeon HD 5970, FEM, Finite element method, Heterogeneous systems, Image processing, Image reconstruction, Linear Algebra, Medicine, nVidia, Tesla C2070, Tesla S1070, Tomography

February 9, 2013 by hgpu

Effectiveness of program transformations and compilers for directive-based GPU programming models

Swapnil Avinash Ghike

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Optimization, Performance, Tesla X2090, Thesis

February 9, 2013 by hgpu

Betweenness Centrality on GPUs and Heterogeneous Architectures

Ahmet Erdem Sariyuce, Kamer Kaya, Erik Saule, Umit V. Catalyurek

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Tags: Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, Package, Tesla C2050, Virtualization

February 7, 2013 by hgpu

Implementation of Fast Artificial Neural Network for Pattern Classification on Heterogeneous System

Devendra Singh Bharangar, Amit Doeger, Yogesh Kumar Mittal

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Tags: ATI, Computer science, Heterogeneous systems, Neural networks, nVidia, OpenCL

February 6, 2013 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

An efficient scheduling scheme using estimated execution time for heterogeneous computing systems

Scheduling a Parallel Sparse Direct Solver to Multiple GPUs

An abstract object oriented runtime system for heterogeneous parallel architecture

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

Adaptation of the MapReduce programming framework to compute-intensive data-analytics kernels

Distributed multi-node, multi-GPU, heterogeneous system for 3D image reconstruction in Electrical Capacitance Tomography – network performance and application analysis

Effectiveness of program transformations and compilers for directive-based GPU programming models

Betweenness Centrality on GPUs and Heterogeneous Architectures

Implementation of Fast Artificial Neural Network for Pattern Classification on Heterogeneous System

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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