high performance computing on graphics processing units: hgpu.org

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Sigma*: Symbolic Learning of Input-Output Specifications

Matko Botincan, Domagoj Babic

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Programming Languages

November 10, 2012 by hgpu

GPU Virtualization

Kristoffer Robin Stokke

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia Quadro NVS 295, Package, Python, Thesis, Virtualization

November 7, 2012 by hgpu

An Intermediate Library for Multi-GPUs Computing Skeletons

Le Duc Tung, Nguyen Huu Duc, Pham Tuan Anh, Ngo Huy Hoang, Nguyen Minh Thap

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Tags: Code generation, Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 295

November 1, 2012 by hgpu

Mapping a Dataflow Programming Model onto Heterogeneous Architectures

Alina Sbirlea

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 580, Tesla C1060, Thesis

September 12, 2012 by hgpu

Lost in Translation: Challenges in Automating CUDA-to-OpenCL Translation

Paul Sathre, Mark Gardner, Wu-chun Feng

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL

September 8, 2012 by hgpu

Supporting Heterogenous Computing Environments in SaC

Miguel Diogo, Clemens Grelck

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia

September 8, 2012 by hgpu

GPUVerify: A Verifier for GPU Kernels

Adam Betts, Nathan Chong, Alastair F. Donaldson, Shaz Qadeer, Paul Thomson

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Tags: ARM, ATI, ATI Radeon HD 7970, Code generation, Computer science, CUDA, nVidia, OpenCL, Package, Performance, Tesla C2050

August 28, 2012 by hgpu

Efficient Dynamic Program Monitoring on Multi-Core Platforms

Guojin He

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro FX 5800, Performance, Security, Thesis

August 26, 2012 by hgpu

Rootbeer: Seamlessly using GPUs from Java

Philip C. Pratt-Szeliga, James W. Fawcett, Roy D. Welch

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Tags: Code generation, Computer science, CUDA, Java, nVidia, OpenCL, Package, Tesla C2050

August 17, 2012 by hgpu

Automated Tool to Generate Parallel CUDA code from a Serial C Code

Akhil Jindal, Nikhil Jindal, Divyashikha Sethia

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce 8400 GS

August 2, 2012 by hgpu

Sigma*: Symbolic Learning of Stream Filters

Matko Botincan, Domagoj Babic

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 460

July 29, 2012 by hgpu

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

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

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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

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

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high performance computing on graphics processing units: hgpu.org

Sigma*: Symbolic Learning of Input-Output Specifications

GPU Virtualization

An Intermediate Library for Multi-GPUs Computing Skeletons

Mapping a Dataflow Programming Model onto Heterogeneous Architectures

Lost in Translation: Challenges in Automating CUDA-to-OpenCL Translation

Supporting Heterogenous Computing Environments in SaC

GPUVerify: A Verifier for GPU Kernels

Efficient Dynamic Program Monitoring on Multi-Core Platforms

Rootbeer: Seamlessly using GPUs from Java

Automated Tool to Generate Parallel CUDA code from a Serial C Code

Sigma*: Symbolic Learning of Stream Filters

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

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

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