high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia Quadro K 2200

Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers

Martin Svedin, Steven W. D. Chien, Gibson Chikafa, Niclas Jansson, Artur Podobas

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Tags: Benchmarking, Computer science, MPI, nVidia, nVidia GeForce GTX 1050 Ti, nVidia Quadro K 2200, Tesla A100, Tesla K80, Tesla P100, Tesla V100

June 20, 2021 by hgpu

Syntix: A Profiling Based Resource Estimator for CUDA Kernels

Maria Papadaki, Yannis Sfakianakis, Christos Kozanitis, Angelos Bilas

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Tags: Computer science, CUDA, GPU cluster, Grid, nVidia, nVidia Quadro K 2200

October 6, 2019 by hgpu

A Machine-Learning Framework for Design for Manufacturability

Aditya Balu, Sambit Ghadai, Gavin Young, Soumik Sarkar, Adarsh Krishnamurthy

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Tags: CNN, Computer science, Deep learning, Keras, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Quadro K 2200

March 9, 2017 by hgpu

MCBooster: a library for fast Monte Carlo generation of phase-space decays on massively parallel platforms

A. A. Alves Jr, M. D. Sokoloff

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Tags: Computational Physics, CUDA, High Energy Physics - Experiment, High Energy Physics - Phenomenology, Intel Xeon Phi, Monte Carlo simulation, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan Z, nVidia Quadro K 2200, OpenMP, Package, Physics, Tesla K40

February 22, 2017 by hgpu

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Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

MapReduce for Counting Word Frequencies with MPI and GPUs

CoDL: Efficient CPU-GPU Co-execution for Deep Learning Inference on Mobile Devices

SYCLCOMP Utilities

On the Compilation Performance of Current SYCL Implementations

M1 GPUs for (scientific) computations in C++

Seamless GPU acceleration for C++ based physics with the Metal Shading Language on Apple’s M series unified chips

CUB: Cooperative primitives for CUDA C++

Onesweep: A Faster Least Significant Digit Radix Sort for GPUs

Simulator and workload generator for Edge-to-Cloud environments

FELARE: Fair Scheduling of Machine Learning Applications on Heterogeneous Edge Systems

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high performance computing on graphics processing units: hgpu.org

Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers

Syntix: A Profiling Based Resource Estimator for CUDA Kernels

A Machine-Learning Framework for Design for Manufacturability

MCBooster: a library for fast Monte Carlo generation of phase-space decays on massively parallel platforms

Recent source codes

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Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

MapReduce for Counting Word Frequencies with MPI and GPUs

CoDL: Efficient CPU-GPU Co-execution for Deep Learning Inference on Mobile Devices

SYCLCOMP Utilities

M1 GPUs for (scientific) computations in C++

CUB: Cooperative primitives for CUDA C++

Simulator and workload generator for Edge-to-Cloud environments

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