high performance computing on graphics processing units: hgpu.org

hgpu.org » Benchmarking

Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators

Yunsup Lee, Rimas Avizienis, Alex Bishara, Richard Xia, Derek Lockhart, Christopher Batten, Krste Asanovic

View

Download (PDF)

Tags: Benchmarking, Computer science, Hardware Architecture

September 7, 2011 by hgpu

Using Graphics Processing Units for Logic Simulation of Electronic Designs

Alper Sen, Baris Aksanli, Murat Bozkurt

View

Download (PDF)

Tags: Algorithms, Benchmarking, Computer science, CUDA, Electronic design automation, nVidia, nVidia Quadro FX 3800, Optimization

September 2, 2011 by hgpu

GPU Versus FPGA for High Productivity Computing

David H. Jones, Adam Powell, Christos-Savvas Bouganis, Peter Y. K. Cheung

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285

September 2, 2011 by hgpu

Parallel hierarchical cross entropy optimization for on-chip decap budgeting

Xueqian Zhao, Yonghe Guo, Zhuo Feng, Shiyan Hu

View

Download (PDF)

Tags: Algorithms, Benchmarking, CAD, Computer science, CUDA, Nonlinear optimization, nVidia, nVidia GeForce GTX 285, Optimization, Probability

September 1, 2011 by hgpu

Bounding the effect of partition camping in GPU kernels

Ashwin M. Aji, Mayank Daga, Wu-chun Feng

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, Performance

August 23, 2011 by hgpu

Benchmarking and modelling of POWER7, Westmere, BG/P, and GPUs: an industry case study

J. A. Herdman, W. P. Gaudin, D. Turland, S. D. Hammond

View

Download (PDF)

Tags: ATI, ATI Radeon HD 5870, Benchmarking, Computer science, MPI, nVidia, nVidia GeForce GTX 285, OpenCL, Performance, Tesla C1060

August 19, 2011 by hgpu

Energy-aware metrics for benchmarking heterogeneous systems

Simon McIntosh-Smith, Terry Wilson, Jon Crisp, Amaurys Avila Ibarra, Richard B. Sessions

View

Download (PDF)

Tags: Benchmarking, Computer science, Energy-efficient computing, Heterogeneous systems, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Tesla C2050

August 18, 2011 by hgpu

THOR: A Transparent Heterogeneous Open Resource framework

J.L. Vazquez-Poletti, J. Perhac, J. Ryan, A.C. Elster

View

Download (PDF)

Tags: Algorithms, Benchmarking, Cloud, Computer science, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 470, OpenCL, Tesla S1070

August 10, 2011 by hgpu

Performance evaluation and optimization of random memory access on multicores with high productivity

Vaibhav Saxena, Yogish Sabharwal, Pramod Bhatotia

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia Quadro FX 4600, Optimization

August 10, 2011 by hgpu

AES finalists implementation for GPU and multi-core CPU based on OpenCL

Xingliang Wang, Xiaochao Li, Mei Zou, Jun Zhou

Tags: AES, Benchmarking, Computer science, CUDA, nVidia, OpenCL, Security

August 8, 2011 by hgpu

A simple and flexible volume rendering framework for graphics-hardware-based raycasting

Simon Stegmaier, Magnus Strengert, Thomas Klein, Thomas Ertl

View

Download (PDF)

Source codes

Tags: 3D Graphics and Realism, Benchmarking, Computer science, Image generation, nVidia, nVidia GeForce 6800 GT, OpenGL, Package, Raytracing, Rendering

August 7, 2011 by hgpu

Enabling active storage on parallel I/O software stacks

Seung Woo Son, Samuel Lang, Philip Carns, Robert Ross, Rajeev Thakur, Berkin Ozisikyilmaz, Prabhat Kumar, Wei-Keng Liao, Alok Choudhary

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, GPU cluster, MPI, nVidia, Tesla C1060

August 6, 2011 by hgpu

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators

Using Graphics Processing Units for Logic Simulation of Electronic Designs

GPU Versus FPGA for High Productivity Computing

Parallel hierarchical cross entropy optimization for on-chip decap budgeting

Bounding the effect of partition camping in GPU kernels

Benchmarking and modelling of POWER7, Westmere, BG/P, and GPUs: an industry case study

Energy-aware metrics for benchmarking heterogeneous systems

Performance evaluation and optimization of random memory access on multicores with high productivity

AES finalists implementation for GPU and multi-core CPU based on OpenCL

A simple and flexible volume rendering framework for graphics-hardware-based raycasting

Enabling active storage on parallel I/O software stacks

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

Most viewed papers (last 30 days)