high performance computing on graphics processing units: hgpu.org

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Efficient Resource Scheduling for Big Data Processing on Accelerator-based Heterogeneous Systems

Ayman Tarakji, David Hebbeker, Lyubomir Georgiev

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Tags: AMD FirePro S10000, AMD FirePro S7000, ATI, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla C2050

May 16, 2015 by hgpu

Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs

George Teodoro, Tahsin Kurc, Guilherme Andrade, Jun Kong, Renato Ferreira, Joel Saltz

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Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, Performance, Tesla K20

May 16, 2015 by hgpu

Workload Aware Algorithms for Heterogeneous Platforms

Kishore Kothapalli, Sivaramakrishna Indarapu, Shashank Sharma, Dip Sankar Banerjee, Rohit Nigam

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GT 520, nVidia GeForce GTX 580, Performance

May 5, 2015 by hgpu

Fine-Grained Synchronizations and Dataflow Programming on GPUs

Ang Li, Gert-Jan van den Braak, Henk Corporaa, Akash Kumar

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 570, Performance, PTX

May 3, 2015 by hgpu

An efficient midpoint-radius representation format to deal with symmetric fuzzy numbers

Manuel Marin, David Defour, Federico Milano

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

April 20, 2015 by hgpu

Benchmarking the cost of thread divergence in CUDA

Piotr Bialas, Adam Strzelecki

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 610, nVidia GeForce GT 755 M, nVidia GeForce GTX 480, nVidia GeForce GTX 650 M, nVidia GeForce GTX 770, nVidia GeForce GTX 850 M, Performance

April 8, 2015 by hgpu

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

Kamran Karimi

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Tags: ATI, Computer science, OpenCL, OpenMP, Performance

March 25, 2015 by hgpu

Raising the Bar for Using GPUs in Software Packet Processing

Anuj Kalia, Dong Zhou, Michael Kaminsky, David G. Andersen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 650 Ti, nVidia GeForce GTX 980, Performance, Tesla K20

March 22, 2015 by hgpu

CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

Weifeng Liu, Brian Vinter

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Source codes

Tags: Algorithms, AMD Radeon R9 290X, Benchmarking, Computer science, CUDA, Intel Xeon Phi, Mathematical Software, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Performance, Sparse matrix

March 20, 2015 by hgpu

The More We Share, The More We Have: Improving GPU performance through Register Sharing

Vishwesh Jatala, Jayvant Anantpur, Amey Karkare

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, Performance

March 20, 2015 by hgpu

An Empirical Performance Evaluation of GPU-Enabled Graph-Processing Systems

Yong Guo, Ana Lucia Varbanescu, Alexandru Iosup, Dick Epema

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Performance, Tesla K20

March 8, 2015 by hgpu

HPerf: A Lightweight Profiler for Task Distribution on CPU+GPU Platforms

Joo Hwan Lee, Nimit Nigania, Hyesoon Kim, Bevin Brett

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia Quadro 2000, OpenCL, Performance

March 8, 2015 by hgpu

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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high performance computing on graphics processing units: hgpu.org

Efficient Resource Scheduling for Big Data Processing on Accelerator-based Heterogeneous Systems

Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs

Workload Aware Algorithms for Heterogeneous Platforms

Fine-Grained Synchronizations and Dataflow Programming on GPUs

An efficient midpoint-radius representation format to deal with symmetric fuzzy numbers

Benchmarking the cost of thread divergence in CUDA

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

Raising the Bar for Using GPUs in Software Packet Processing

CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

The More We Share, The More We Have: Improving GPU performance through Register Sharing

An Empirical Performance Evaluation of GPU-Enabled Graph-Processing Systems

HPerf: A Lightweight Profiler for Task Distribution on CPU+GPU Platforms

Recent source codes

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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