high performance computing on graphics processing units: hgpu.org

hgpu.org » Storage system

Opportunities for Nonvolatile Memory Systems in Extreme-Scale High Performance Computing

Jeffrey S. Vetter, Sparsh Mittal

View

Download (PDF)

Tags: cpu, Energy-efficient computing, GPU, high performance computing, Memory, Storage system

January 21, 2015 by sparsh0mittal

Harnessing GPU Computing in System-Level Software

Weibin Sun

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Security, Storage system, Thesis

September 30, 2014 by hgpu

GPUdrive: Reconsidering Storage Accesses for GPU Acceleration

Mustafa Shihab, Karl Taht, Myoungsoo Jung

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Storage system

July 16, 2014 by hgpu

Realizing Accelerated Cost-Effective Distributed RAID

Aleksandr Khasymski, M. Mustafa Rafique, Ali R. Butt, Sudharshan S. Vazhkudai, Dimitrios S. Nikolopoulos

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Storage system, Tesla C2070, Tesla X2090

June 13, 2014 by hgpu

Towards High-Performance and Cost-Effective Distributed Storage Systems with Information Dispersal Algorithms

Dongfang Zhao, Kent Burlingame, Corentin Debains, Pedro Alvarez-Tabio, Ioan Raicu

View

Download (PDF)

Tags: Algorithms, Cloud, Computer science, CUDA, nVidia, nVidia GeForce GT 640, Storage system

August 29, 2013 by hgpu

Parallel Memory Defragmentation on a GPU

Ronald Veldema, Michael Philippsen

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 560 Ti, Performance, Storage system

July 6, 2012 by hgpu

On the Use of GPUs in Realizing Cost-Effective Distributed RAID

Aleksandr Khasymski, M. Mustafa Rafique, Ali R. Butt, Sudharshan S. Vazhkudai, Dimitrios S. Nikolopoulos

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, Storage system, Tesla C2070

July 3, 2012 by hgpu

GPUstore: Harnessing GPU Computing for Storage Systems in the OS Kernel

Weibin Sun, Robert Ricci, Matthew L. Curry

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Data recovery, nVidia, nVidia GeForce GTX 480, Package, Security, Storage system

March 26, 2012 by hgpu

Shredder: GPU-Accelerated Incremental Storage and Computation

Pramod Bhatotia, Rodrigo Rodrigues, Akshat Verma

View

Download (PDF)

Tags: Cloud, Computer science, CUDA, MapReduce, nVidia, Storage system, Tesla C2050

February 24, 2012 by hgpu

GPUs as Storage System Accelerators

Samer Al-Kiswany, Abdullah Gharaibeh, Matei Ripeanu

View

Download (PDF)

Tags: Computer science, CUDA, Hashing, nVidia, Security, Storage system, Tesla C2050

February 17, 2012 by hgpu

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

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Opportunities for Nonvolatile Memory Systems in Extreme-Scale High Performance Computing

Harnessing GPU Computing in System-Level Software

GPUdrive: Reconsidering Storage Accesses for GPU Acceleration

Realizing Accelerated Cost-Effective Distributed RAID

Parallel Memory Defragmentation on a GPU

On the Use of GPUs in Realizing Cost-Effective Distributed RAID

GPUstore: Harnessing GPU Computing for Storage Systems in the OS Kernel

GPUs as Storage System Accelerators

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

Most viewed papers (last 30 days)