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Energy efficiency vs. performance of the numerical solution of PDEs: an application study on a low-power ARM-based cluster

Dominik Goeddeke, Dimitri Komatitsch, Markus Geveler, Dirk Ribbrock, Nikola Rajovic, Nikola Puzovic, Alex Ramirez

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Tags: ARM, Differential equations, Energy-efficient computing, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, Partial differential equations, PDEs, Spectral elements

November 26, 2012 by hgpu

Power and Performance Analysis of GPU-Accelerated Systems

Yuki Abe, Hiroshi Sasaki, Martin Peres, Koji Inoue, Kazuaki Murakami, Shinpei Kato

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 480, Package

September 6, 2012 by hgpu

GreenGPU: A Holistic Approach to Energy Efficiency in GPU-CPU Heterogeneous Architectures

Kai Ma, Xue Li, Wei Chen, Chi Zhang, Xiaorui Wang

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Tags: Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX

June 26, 2012 by hgpu

Energy Efficiency Analysis of GPUs

Juan M. Cebrian, Gines D. Guerrero, Jose M. Garcia

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 465, nVidia GeForce GTX 480

June 15, 2012 by hgpu

Tree Structured Analysis on GPU Power Study

Jianmin Chen, Bin Li, Ying Zhang, Lu Peng, Jih-kwon Peir

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 280

April 23, 2012 by hgpu

High-Performance Energy-Efficient Multicore Embedded Computing

Arslan Munir, Sanjay Ranka, Ann Gordon-Ross

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Tags: Computer science, Embedded high-performance computing, Energy-efficient computing, Review

April 6, 2012 by hgpu

An Energy Consumption Model for GPU Computing at Instruction Level

Haifeng Wang, Qingkui Chen

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Tags: Code generation, Computer science, Energy-efficient computing, nVidia, nVidia GeForce GTX 280, PTX

February 27, 2012 by hgpu

Power-Efficient Time-Sensitive Mapping in Heterogeneous Systems

Cong Liu, Jian Li, Wei Huang, Juan Rubio, Evan Speight, Xiaozhu Lin

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Tags: ATI, ATI Radeon HD 5770, Computer science, Energy-efficient computing, Heterogeneous systems, OpenCL

February 26, 2012 by hgpu

A Hierarchical Thread Scheduler and Register File for Energy-efficient Throughput Processors

Mark Gebhart, Daniel R. Johnson, David Tarjan, Stephen W. Keckler, William J. Dally, Erik Lindholm, Kevin Skadron

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia

February 22, 2012 by hgpu

An Energy-Efficient Heterogeneous System for Embedded Learning and Classification

Abhinandan Majumdar, Srihari Cadambi, Srimat T. Chakradhar

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Tags: Computer science, Energy-efficient computing, FPGA, Heterogeneous systems, nVidia, nVidia ION, Tesla C1070

January 20, 2012 by hgpu

Power Profiling and Optimization for Heterogeneous Multi-Core Systems

Kuen Hung Tsoi, Wayne Luk

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Tags: Computer science, CUDA, Design space exploration, Energy-efficient computing, FPGA, Heterogeneous systems, N-body simulation, nVidia, Optimization, Tesla C1060

January 19, 2012 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Energy efficiency vs. performance of the numerical solution of PDEs: an application study on a low-power ARM-based cluster

Power and Performance Analysis of GPU-Accelerated Systems

GreenGPU: A Holistic Approach to Energy Efficiency in GPU-CPU Heterogeneous Architectures

Energy Efficiency Analysis of GPUs

Tree Structured Analysis on GPU Power Study

High-Performance Energy-Efficient Multicore Embedded Computing

An Energy Consumption Model for GPU Computing at Instruction Level

Power-Efficient Time-Sensitive Mapping in Heterogeneous Systems

A Hierarchical Thread Scheduler and Register File for Energy-efficient Throughput Processors

An Energy-Efficient Heterogeneous System for Embedded Learning and Classification

Power Profiling and Optimization for Heterogeneous Multi-Core Systems

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

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