high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Kargus: a Highly-scalable Software-based Intrusion Detection System

Muhammad Jamshed, Jihyung Lee, Sangwoo Moon, Insu Yun, Deokjin Kim, Sungryoul Lee, Yung Yi, KyoungSoo Park

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Security

August 9, 2012 by hgpu

Coordinated system level resource management for heterogeneous many-core platforms

Vishakha Gupta

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GTX, Thesis

August 6, 2012 by hgpu

Power Management for GPU-CPU Heterogeneous Systems

Xue Li

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, Thesis

August 3, 2012 by hgpu

Interference-driven resource management for GPU-based heterogeneous clusters

Rajat Phull, Cheng-Hong Li, Kunal Rao, Srihari Cadambi, Srimat Chakradhar

View

Download (PDF)

Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, PC cluster, Performance, Tesla C2050

August 1, 2012 by hgpu

accULL: An User-directed Approach to Heterogeneous Programming

Ruyman Reyes, Ivan Lopez, Juan J. Fumero, Francisco de Sande

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Package, Python, Tesla C1060, Tesla C2050

July 31, 2012 by hgpu

A virtual memory based runtime to support multi-tenancy in clusters with GPUs

Michela Becchi, Kittisak Sajjapongse, Ian Graves, Adam Procter, Vignesh Ravi, Srimat Chakradhar

View

Download (PDF)

Tags: Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, PC cluster, Tesla C1060, Tesla C2050, Virtualization

July 27, 2012 by hgpu

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

Jungwon Kim, Sangmin Seo, Jun Lee, Jeongho Nah, Gangwon Jo, Jaejin Lee

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package, Programming Languages, Programming techniques

July 26, 2012 by hgpu

Source-to-source transformations for irregular and multithreaded code optimization

Julien Jaeger

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, Thesis

July 24, 2012 by hgpu

LBCL: multi-device automatic load balancing

Carlos S. de la Lama, Pablo Toharia, Oscar D. Robles, Jose Luis Bosque

View

Download (PDF)

Tags: Computer science, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL

July 23, 2012 by hgpu

Scaling CUDA for Distributed Heterogeneous Processors

Siu Kwan Lam

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, Memory model, MPI, nVidia, Package, PTX, Python, Thesis

July 20, 2012 by hgpu

GPU-Accelerated Point-Based Color Bleeding

Ryan Daniel Schmitt

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 5970, Computer science, Heterogeneous systems, OpenGL, Rasterization, Thesis

July 20, 2012 by hgpu

Optimizing MapReduce for GPUs with effective shared memory usage

Linchuan Chen, Gagan Agrawal

View

Download (PDF)

Tags: Computer science, Heterogeneous systems, MapReduce, Memory, nVidia, nVidia Quadro FX 5800, Performance

July 16, 2012 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Kargus: a Highly-scalable Software-based Intrusion Detection System

Coordinated system level resource management for heterogeneous many-core platforms

Power Management for GPU-CPU Heterogeneous Systems

Interference-driven resource management for GPU-based heterogeneous clusters

accULL: An User-directed Approach to Heterogeneous Programming

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

Source-to-source transformations for irregular and multithreaded code optimization

LBCL: multi-device automatic load balancing

Scaling CUDA for Distributed Heterogeneous Processors

GPU-Accelerated Point-Based Color Bleeding

Optimizing MapReduce for GPUs with effective shared memory usage

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)