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Comparison and Analysis of GPU Energy Efficiency For CUDA and OpenCL

Joe Jackson

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Tags: Computer science, CUDA, Energy-efficient computing, Matrix multiplication, nVidia, nVidia GeForce 9800 GT, OpenCL

July 8, 2013 by hgpu

An Energy Efficient GPGPU Memory Hierarchy with Tiny Incoherent Caches

Alamelu Sankaranarayanan, Ehsan K. Ardestani, Jose Luis Briz, Jose Renau

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Tags: Computer science, CUDA, Energy-efficient computing, GPGPU-sim, Memory, nVidia, OpenCL

June 24, 2013 by hgpu

Exploring GPGPUs Workload Characteristics and Power Consumption

Sohan Lal, Jan Lucas, Mauricio Alvarez-Mesa, Ahmed Elhossini, Ben Juurlink

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Tags: Computer science, CUDA, Energy-efficient computing, GPGPU-sim, nVidia, nVidia GeForce GTX 580, Performance

June 22, 2013 by hgpu

Performance Analysis on Energy Efficient High-Performance Architectures

Roman Iakymchuk, Francois Trahay

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

June 16, 2013 by hgpu

Cost-Effective Soft-Error Protection for SRAM-Based Structures in GPGPUs

Jingweijia Tan, Zhi Li, Xin Fu

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

June 13, 2013 by hgpu

How a Single Chip Causes Massive Power Bills. GPUSimPow: A GPGPU Power Simulator

Jan Lucas, Sohan Lal, Michael Andersch, Mauricio Alvarez-Mesa, Ben Juurlink

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Source codes

Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 580, Package

June 7, 2013 by hgpu

pVOCL: Power-Aware Dynamic Placement and Migration in Virtualized GPU Environments

Palden Lama, Yan Li, Ashwin M. Aji, Pavan Balaji, James Dinan, Shucai Xiao, Yunquan Zhang, Wu-chun Feng, Rajeev Thakur, Xiaobo Zhou

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Tags: Computer science, Energy-efficient computing, nVidia, OpenCL, Tesla C1060, Virtualization

April 8, 2013 by hgpu

The Stencil Processing Unit: GPGPU Done Right

Sanjay Rajopadhye, Guillaume Iooss, Tomofumi Yuki, Dan Connors

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Tags: Computer science, Energy-efficient computing

April 3, 2013 by hgpu

Exploring power efficiency and optimizations targeting heterogeneous applications

Yash Sanjeev Ukidave

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Tags: AMD Fusion, ATI, ATI Radeon HD 7770, Computer science, Energy-efficient computing, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, Thesis

March 16, 2013 by hgpu

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Shuaiwen Song, Chunyi Su, Barry Rountree, Kirk W. Cameron

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Tags: Biomolecules, Computer science, CUDA, Electrostatics, Energy-efficient computing, GPU cluster, Heterogeneous systems, Machine learning, nVidia, Tesla C2075, Tesla M2090

February 18, 2013 by hgpu

Scan Test Power Simulation on GPGPUs

S. Holst, E. Schneider, H.-J. Wunderlich

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

January 18, 2013 by hgpu

Inter-Warp Instruction Temporal Locality in Deep-Multithreaded GPUs

Ahmad Lashgar, Amirali Baniasadi, Ahmad Khonsari

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Tags: Computer science, Energy-efficient computing, GPGPU-sim, nVidia, Tesla

January 17, 2013 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

Comparison and Analysis of GPU Energy Efficiency For CUDA and OpenCL

An Energy Efficient GPGPU Memory Hierarchy with Tiny Incoherent Caches

Exploring GPGPUs Workload Characteristics and Power Consumption

Performance Analysis on Energy Efficient High-Performance Architectures

Cost-Effective Soft-Error Protection for SRAM-Based Structures in GPGPUs

How a Single Chip Causes Massive Power Bills. GPUSimPow: A GPGPU Power Simulator

pVOCL: Power-Aware Dynamic Placement and Migration in Virtualized GPU Environments

The Stencil Processing Unit: GPGPU Done Right

Exploring power efficiency and optimizations targeting heterogeneous applications

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Scan Test Power Simulation on GPGPUs

Inter-Warp Instruction Temporal Locality in Deep-Multithreaded GPUs

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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