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A compiler toolkit for array-based languages targeting CPU/GPU hybrid systems

Rahul Garg, Laurie Hendren

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Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 7970, Code generation, Compilers, Computer science, OpenCL, Package, Python, Tesla C2050

November 26, 2012 by hgpu

Architectural Considerations for Compiler-guided Unroll-and-Jam of CUDA Kernels

Apan Qasem

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Tags: Compilers, Computer science, CUDA, Memory model, nVidia, nVidia GeForce 9800 GT, Tesla C2050

November 8, 2012 by hgpu

Kite: Braided Parallelism for Heterogeneous Systems

J. Garrett Morris, Benedict R. Gaster, Lee Howes

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Tags: Compilers, Computer science, Heterogeneous systems, OpenCL, Programming techniques

November 5, 2012 by hgpu

Enhancing Productivity and Performance Portability of General-Purpose Parallel Programming

Alexandros Tzannes

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Tags: Compilers, Computer science, Programming techniques, Thesis

October 17, 2012 by hgpu

Extendable Pattern-Oriented Optimization Directives (extended version)

Huimin Cui, Jingling Xue, Lei Wang, Yang Yang, Xiaobing Feng, Dongrui Fan

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Tags: Compilers, Computer science, nVidia, nVidia GeForce GTX 285, Optimization, Performance

October 13, 2012 by hgpu

A Unified Optimizing Compiler Framework for Different GPGPU Architectures

Yi Yang, Ping Xiang, Jingfei Kong, Mike Mantor, Huiyang Zhou

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Tags: ATI, ATI Radeon HD 5870, Compilers, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, Optimization, Package, Programming Languages

August 27, 2012 by hgpu

Fixing Performance Bugs: An Empirical Study of Open-Source GPGPU Programs

Yi Yang, Ping Xiang, Mike Mantor, Huiyang Zhou

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Tags: ATI, ATI Radeon HD 5870, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, Performance

August 21, 2012 by hgpu

Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission

Haicheng Wu, Gregory Diamos, Ashwin Lele, Jin Wang, Srihari Cadambi, Sudhakar Yalamanchili, Srimat Chakradhar

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Tags: Compilers, Computer science, CUDA, Databases, nVidia, Optimization, Tesla C2070

August 9, 2012 by hgpu

A Comparative Study of OpenACC Implementations

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

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenACC, OpenCL, OpenMP, Performance, Tesla C2050

July 23, 2012 by hgpu

Compiling a high-level language for GPUs: (via language support for architectures and compilers)

Christophe Dubach, Perry Cheng, Rodric Rabbah, David F. Bacon, Stephen J. Fink

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Tags: ATI, ATI Radeon HD 5970, Compilers, Computer science, CUDA, Heterogeneous systems, Java, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 580, OpenCL, Programming Languages

June 26, 2012 by hgpu

Hierarchical overlapped tiling

Xing Zhou, Jean-Pierre Giacalone, Maria Jesus Garzaran, Robert H Kuhn, Yang Ni, David Padua

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Tags: Compilers, Computer science, OpenCL, Performance

June 23, 2012 by hgpu

High-Level Support for Pipeline Parallelism on Many-Core Architectures

Siegfried Benkner, Enes Bajrovic, Erich Marth, Martin Sandrieser, Raymond Namyst, Samuel Thibault

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480

May 20, 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

A compiler toolkit for array-based languages targeting CPU/GPU hybrid systems

Architectural Considerations for Compiler-guided Unroll-and-Jam of CUDA Kernels

Kite: Braided Parallelism for Heterogeneous Systems

Enhancing Productivity and Performance Portability of General-Purpose Parallel Programming

Extendable Pattern-Oriented Optimization Directives (extended version)

A Unified Optimizing Compiler Framework for Different GPGPU Architectures

Fixing Performance Bugs: An Empirical Study of Open-Source GPGPU Programs

Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission

A Comparative Study of OpenACC Implementations

Compiling a high-level language for GPUs: (via language support for architectures and compilers)

Hierarchical overlapped tiling

High-Level Support for Pipeline Parallelism on Many-Core Architectures

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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