high performance computing on graphics processing units: hgpu.org

hgpu.org » PTX

Usable assembly language for GPUs: a success story

Daniel J. Bernstein, Hsieh-Chung Chen, Chen-Mou Cheng, Tanja Lange, Ruben Niederhagen, Peter Schwabe, Bo-Yin Yang

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Performance, PTX, Security

March 18, 2012 by hgpu

An Energy Consumption Model for GPU Computing at Instruction Level

Haifeng Wang, Qingkui Chen

View

Download (PDF)

Tags: Code generation, Computer science, Energy-efficient computing, nVidia, nVidia GeForce GTX 280, PTX

February 27, 2012 by hgpu

Symbolic Testing of OpenCL Code

Peter Collingbourne, Cristian Cadar, Paul H. J. Kelly

View

Download (PDF)

Source codes

Tags: Benchmarking, Code generation, Computer science, nVidia, OpenCL, Package, PTX, Tesla C1060

February 8, 2012 by hgpu

Solving Discrete Logarithms in Smooth-Order Groups with CUDA

Ryan Henry, Ian Goldberg

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, Package, PTX, Security, Tesla M2050

January 29, 2012 by hgpu

A Compile-Time Managed Multi-Level Register File Hierarchy

Mark Gebhart, Stephen W. Keckler, William J. Dally

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, nVidia, Optimization, PTX

January 19, 2012 by hgpu

Experiences Developing the OpenUH Compiler and Runtime Infrastructure

Barbara Chapman, Deepak Eachempati, Oscar Hernandez

View

Download (PDF)

Source codes

Tags: Code generation, Compilers, Computer science, nVidia, Package, PTX

December 19, 2011 by hgpu

A Translation Framework for Executing the Sequential Binary Code on CPU/GPU Based Architectures

Erzhou Zhu, Haibing Guan, Guoxing Dong, Yindong Yang, Hongbo Yang

View

Download (PDF)

Tags: Benchmarking, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, PTX

December 18, 2011 by hgpu

Code Optimization Techniques for Graphics Processing Units

Fernando Magno Quintao Pereira

View

Download (PDF)

Source codes

Tags: Algorithms, Book, Code generation, Computer science, CUDA, nVidia, nVidia GeForce 9400 M, Optimization, Package, Programming techniques, PTX, Tutorial

December 17, 2011 by hgpu

Divergence Analysis with Affine Constraints

Diogo Sampaio, Rafael Martins, Fernando Magno Quintao Pereira, Sylvain Collange

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 570, Optimization, Package, PTX

December 13, 2011 by hgpu

Design and Implementation of a PTX Emulation Library

Albert Claret Exojo

View

Download (PDF)

Tags: Computer science, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Performance, PTX, Tesla S870, Thesis

November 18, 2011 by hgpu

SIMD Re-Convergence At Thread Frontiers

Gregory Diamos, Andrew Kerr, Haicheng Wu, Sudhakar Yalamanchili, Benjamin Ashbaugh, Subramaniam Maiyuran

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Performance, Programming Languages, PTX

October 31, 2011 by hgpu

The Model of Computation of CUDA and its Formal Semantics

Axel Habermaier

View

Download (PDF)

Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 480, PTX, Thesis

October 25, 2011 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

Usable assembly language for GPUs: a success story

An Energy Consumption Model for GPU Computing at Instruction Level

Symbolic Testing of OpenCL Code

Solving Discrete Logarithms in Smooth-Order Groups with CUDA

A Compile-Time Managed Multi-Level Register File Hierarchy

Experiences Developing the OpenUH Compiler and Runtime Infrastructure

A Translation Framework for Executing the Sequential Binary Code on CPU/GPU Based Architectures

Code Optimization Techniques for Graphics Processing Units

Divergence Analysis with Affine Constraints

Design and Implementation of a PTX Emulation Library

SIMD Re-Convergence At Thread Frontiers

The Model of Computation of CUDA and its Formal Semantics

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)