high performance computing on graphics processing units: hgpu.org

hgpu.org » Tesla S1070

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

Bo Wu, Eddy Z. Zhang, Xipeng Shen

View

Download (PDF)

Tags: Algorithms, Benchmarking, CMP, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Tesla S1070

September 30, 2011 by hgpu

GPU Accelerated Computation of the ICON Model

Christian Conti, William Sawyer

View

Download (PDF)

Tags: ATI, ATI Radeon HD 6990, Earth and Space Sciences, nVidia, nVidia GeForce GTX 285, OpenCL, Tesla M2050, Tesla S1070, Weather prediction

September 27, 2011 by hgpu

Hauberk: Lightweight Silent Data Corruption Error Detector for GPGPU

Keun Soo Yim, Cuong Pham, Mushfiq Saleheen, Zbigniew Kalbarczyk, Ravishankar Iyer

View

Download (PDF)

Tags: Computer science, CUDA, Error recovery, Fault tolerance, nVidia, Tesla S1070

September 25, 2011 by hgpu

Implementing the PGI Accelerator model

Michael Wolfe

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization, Programming Languages, Tesla C1060, Tesla S1070

August 23, 2011 by hgpu

Maestro: Data Orchestration and Tuning for OpenCL Devices

Kyle Spafford, Jeremy Meredith, Jeffrey Vetter

View

Download (PDF)

Tags: ATI, ATI Radeon HD 5870, Computer science, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Performance, Tesla C1060, Tesla S1070

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

Pricing the American Option Using Reconfigurable Hardware

Chris Wynnyk, Malik Magdon-Ismail

View

Download (PDF)

Tags: Algorithms, CUDA, Finance, Finite difference, FPGA, nVidia, Tesla S1070

August 10, 2011 by hgpu

Data-Aware Task Scheduling on Multi-accelerator Based Platforms

Cedric Augonnet, Jerome Clet-Ortega, Samuel Thibault, Raymond Namyst

View

Download (PDF)

Source codes

Tags: Algorithms, Benchmarking, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, nVidia Quadro FX 5800, Package, Prefetch, Task scheduling, Tesla S1070

July 26, 2011 by hgpu

Out-of-core cone beam reconstruction using multiple GPUs

Fumihiko Ino, Yusuke Okitsu, Taketo Kishi, Syuhei Ohnishi, Kenichi Hagihara

View

Download (PDF)

Tags: Algorithms, CUDA, Image reconstruction, Medicine, nVidia, Tesla S1070

July 24, 2011 by hgpu

Linpack evaluation on a supercomputer with heterogeneous accelerators

Toshio Endo, Akira Nukada, Satoshi Matsuoka, Naoya Maruyama

View

Download (PDF)

Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla S1070

July 17, 2011 by hgpu

A Sparse Matrix Personality for the Convey HC-1

Krishna K. Nagar, Jason D. Bakos

View

Download (PDF)

Tags: Computer science, CUDA, FPGA, nVidia, Performance, Sparse matrix, Tesla S1070

July 14, 2011 by hgpu

Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters

Wenjing Ma, Sriram Krishnamoorthy, Oreste Villa, Karol Kowalski

View

Download (PDF)

Tags: Computational chemistry, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Presentation, Tesla C1070, Tesla S1070

July 7, 2011 by hgpu

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

* * *

high performance computing on graphics processing units: hgpu.org

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

GPU Accelerated Computation of the ICON Model

Hauberk: Lightweight Silent Data Corruption Error Detector for GPGPU

Implementing the PGI Accelerator model

Maestro: Data Orchestration and Tuning for OpenCL Devices

Pricing the American Option Using Reconfigurable Hardware

Data-Aware Task Scheduling on Multi-accelerator Based Platforms

Out-of-core cone beam reconstruction using multiple GPUs

Linpack evaluation on a supercomputer with heterogeneous accelerators

A Sparse Matrix Personality for the Convey HC-1

Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters

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

Most viewed papers (last 30 days)