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A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

Sparsh Mittal

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Tags: Embedded high-performance computing, Energy-efficient computing, FPGA, GPU, Power-efficient computing

January 7, 2015 by sparsh0mittal

GPU: Power vs Performance

Siddhartha Sankar Mondal

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 580, Thesis

January 5, 2015 by hgpu

Bounds on the Energy Consumption of Computational Kernels

Andrew Gearhart

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Tags: Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, Package, Tesla K20, Thesis

November 3, 2014 by hgpu

Energy Evaluation for Applications with Different Thread Affinities on the Intel Xeon Phi

Gary Lawson, Masha Sosonkina, Yuzhong Shen

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Performance

August 15, 2014 by hgpu

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

D. C. Price, M. A. Clark, B. R. Barsdell, R. Babich, L. J. Greenhill

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Tags: Astrophysics, CUDA, Energy-efficient computing, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 780, Package, Performance, Signal processing, Tesla K20

August 1, 2014 by hgpu

Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Computer science, CUDA, Distributed computing, Energy-efficient computing, Heterogeneous systems, nVidia, Tesla K20

July 17, 2014 by hgpu

Energy Efficiency Benefits of Reducing the Voltage Guardband on the Kepler GPU Architecture

Jingwen Leng, Yazhou Zu, Vijay Janapa Reddi

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 680

July 1, 2014 by hgpu

Effect And Analysis of Elastic Fidelity Computing On GPUs

Chetan Arvind Patil, Georgios Tziantzioulis, Nikos Hardavellas

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Tags: Computer science, CUDA, Energy-efficient computing, GPGPU-sim, nVidia, nVidia GeForce GTX 480, OpenCL

June 26, 2014 by hgpu

The Power-Performance Tradeoffs of the Intel Xeon Phi on HPC Applications

Bo Li, Hung-Ching Chang, Shuaiwen Leon Song, Chun-Yi Su, Timmy Meyer, John Mooring, Kirk Cameron

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, nVidia, Performance, Tesla C2050

June 22, 2014 by hgpu

Assessing the Performance-Energy Balance of Graphics Processors for Spectral Unmixing

Sergio Sanchez, German Leon, Antonio Plaza, Enrique S. Quintana-Orti

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Tags: ARM, CUDA, Energy-efficient computing, Image processing, nVidia, nVidia GeForce GTX 480, nVidia Quadro 1000 M, Tesla K20

May 5, 2014 by hgpu

On the Use of Remote GPUs and Low-Power Processors for the Acceleration of Scientific Applications

A. Castello, J. Duato, R. Mayo, A. J. Pena, E. S. Quintana-Orti, V. Roca, F. Silla

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Tags: Bioinformatics, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Virtualization

April 27, 2014 by hgpu

A Survey of Methods For Analyzing and Improving GPU Energy Efficiency

Sparsh Mittal, Jeffrey S. Vetter

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Tags: comparison, Computer science, cpu, CUDA, Energy-efficient computing, FPGA, Hardware Architecture, nVidia

April 18, 2014 by sparsh0mittal

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

GPU: Power vs Performance

Bounds on the Energy Consumption of Computational Kernels

Energy Evaluation for Applications with Different Thread Affinities on the Intel Xeon Phi

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs

Energy Efficiency Benefits of Reducing the Voltage Guardband on the Kepler GPU Architecture

Effect And Analysis of Elastic Fidelity Computing On GPUs

The Power-Performance Tradeoffs of the Intel Xeon Phi on HPC Applications

Assessing the Performance-Energy Balance of Graphics Processors for Spectral Unmixing

On the Use of Remote GPUs and Low-Power Processors for the Acceleration of Scientific Applications

A Survey of Methods For Analyzing and Improving GPU Energy Efficiency

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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