high performance computing on graphics processing units: hgpu.org

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Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter

Jie Li, George Michelogiannakis, Brandon Cook, Dulanya Cooray, Yong Chen

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Tags: Computer science, HPC, nVidia, nVidia A100, Performance

January 22, 2023 by hgpu

BaCO: A Fast and Portable Bayesian Compiler Optimization Framework

Erik Hellsten, Artur Souza, Johannes Lenfers, Rubens Lacouture, Olivia Hsu, Adel Ejjeh, Fredrik Kjolstad, Michel Steuwer, Kunle Olukotun, Luigi Nardi

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Tags: Bayesian, Compilers, Computer science, FPGA, nVidia, OpenCL, Package, Performance, Programming Languages, Tesla K80

January 8, 2023 by hgpu

Understanding the Impact of Input Entropy on FPU, CPU, and GPU Power

Sridutt Bhalachandra, Brian Austin, Samuel Williams, Nicholas J. Wright

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Tags: Computer science, Hardware Architecture, nVidia, nVidia A100, Package, Performance

December 25, 2022 by hgpu

A Study on the Intersection of GPU Utilization and CNN Inference

Jack Kosaian, Amar Phanishayee

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Tags: CNN, Computer science, Deep learning, Neural networks, nVidia, Performance, Tesla V100

December 19, 2022 by hgpu

Fast convolution kernels on pascal GPU with high memory efficiency

Qiong Chang, Masaki Onishi, Tsutomu Maruyama

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Tags: CNN, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Performance

December 4, 2022 by hgpu

Challenges and Techniques for Transparent Acceleration of Unmodified Big Data Applications

Maria Nektaria Xekalaki

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Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 1060, nVidia Quadro GP100, OpenCL, Package, Performance, Tesla V100, Thesis

November 20, 2022 by hgpu

Capturing the Memory Topology of GPUs

Dominik Größler

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce 840 M, nVidia GeForce RTX 2080 Ti, nVidia Quadro P 6000, Package, Performance, PTX, Tesla K20, Tesla V100, Thesis

November 13, 2022 by hgpu

Apple Silicon Performance in Scientific Computing

Connor Kenyon, Collin Capano

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Tags: Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia A100, nVidia V100, OpenCL, Performance

November 6, 2022 by hgpu

A systematic performance study of the parallel programming framework SkePU 3 using HPC-benchmarks

Erik Tedhamre

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Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, OpenCL, OpenMP, Package, Performance

October 30, 2022 by hgpu

gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs

Taha Tekdoğan, Serkan Göktaş, Ayse Yilmazer-Metin

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Tags: Benchmarking, Computer science, CUDA, Machine learning, Neural networks, nVidia, Performance, Tesla V100

October 30, 2022 by hgpu

Dataloader Parameter Tuner: An Automated Dataloader Parameter Tuner for Deep Learning Models

JooYoung Park, DoangJoo Synn, XinYu Piao, Jong-Kook Kim

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 3080 Ti, Performance, Prefetch

October 16, 2022 by hgpu

PMT: Power Measurement Toolkit

Stefano Corda, Bram Veenboer, Emma Tolley

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Tags: AMD Radeon Pro W6600, ATI, Computer science, Energy-efficient computing, HPC, nVidia, nVidia Titan RTX, Package, Performance

October 16, 2022 by hgpu

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FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Pulsar search acceleration using FPGAs and OpenCL templates

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

Fast Merge Tree Computation via SYCL

pocl: Portable Computing Language

Efficient OpenCL system integration of non-blocking FPGA accelerators

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

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high performance computing on graphics processing units: hgpu.org

Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter

BaCO: A Fast and Portable Bayesian Compiler Optimization Framework

Understanding the Impact of Input Entropy on FPU, CPU, and GPU Power

A Study on the Intersection of GPU Utilization and CNN Inference

Fast convolution kernels on pascal GPU with high memory efficiency

Challenges and Techniques for Transparent Acceleration of Unmodified Big Data Applications

Capturing the Memory Topology of GPUs

Apple Silicon Performance in Scientific Computing

A systematic performance study of the parallel programming framework SkePU 3 using HPC-benchmarks

gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs

Dataloader Parameter Tuner: An Automated Dataloader Parameter Tuner for Deep Learning Models

PMT: Power Measurement Toolkit

Recent source codes

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

pocl: Portable Computing Language

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

Python Suite for Advanced General Ensemble Simulations

GPU load-balancing library for regular and irregular computations

Shine compiler for the RISE language

Cramming the training of a (BERT-type) language model into limited compute

oneDNN: oneAPI Deep Neural Network Library

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