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Verified Instruction-Level Energy Consumption Measurement for NVIDIA GPUs

Yehia Arafa, Ammar ElWazir, Abdelrahman ElKanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed Badawy, Gopinath Chennupati, Stephan Eidenbenz, Nandakishore Santhi

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Tags: Computer science, CUDA, Energy-efficient computing, Measurement techniques, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX Titan V, nVidia GeForce GTX Titan X, nVidia Titan RTX, PTX

February 23, 2020 by hgpu

GPU performance comparison for accelerated radar data processing

Chris Fallen, Beau Bellamy, Greg Newby, Brent Watkins

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Tags: Measurement techniques, nVidia, nVidia GeForce GTX 480, OpenCL, Presentation, Signal processing, Tesla M2050

October 4, 2011 by hgpu

Improving processing time for visual measurements of displacements of IPMC actuators using CUDA

K. Tsiakmakis, T. Laopoulos

Tags: CUDA, Image processing, Materials Science, Measurement techniques, nVidia, Physics

June 26, 2011 by hgpu

Evolution of thread-level parallelism in desktop applications

Geoffrey Blake, Ronald G. Dreslinski, Trevor Mudge, Krisztian Flautner

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Tags: Benchmarking, Computer science, Measurement techniques, nVidia, nVidia GeForce GT 120, nVidia GeForce GTX 285, nVidia ION

November 7, 2010 by hgpu

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TorchOpt: an efficient library for differentiable optimization built upon PyTorch

TorchOpt: An Efficient Library for Differentiable Optimization

NaturalCC: An Open-Source Toolkit for Code Intelligence

A Study on Neural-based Code Summarization in Low-resource Settings

mt4g: Memory Topology for GPUs

Capturing the Memory Topology of GPUs

iGniter: an interference-aware GPU resource provisioning framework for achieving predictable performance of DNN inference in the cloud

iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud

pyGSL: A Scalable Library for Graph Structure Learning

pyGSL: A Graph Structure Learning Toolkit

See all packages

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high performance computing on graphics processing units: hgpu.org

Verified Instruction-Level Energy Consumption Measurement for NVIDIA GPUs

GPU performance comparison for accelerated radar data processing

Improving processing time for visual measurements of displacements of IPMC actuators using CUDA

Evolution of thread-level parallelism in desktop applications

Recent source codes

SYCL-DNN: a library implementing neural network algorithms written using SYCL

SW#SYCL

StateMover: a checkpoint-based debugging framework for FPGAs

Flink-TornadoVM-Artifact

Kernel Tuner

TorchOpt: an efficient library for differentiable optimization built upon PyTorch

NaturalCC: An Open-Source Toolkit for Code Intelligence

mt4g: Memory Topology for GPUs

iGniter: an interference-aware GPU resource provisioning framework for achieving predictable performance of DNN inference in the cloud

pyGSL: A Scalable Library for Graph Structure Learning

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