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CU2rCU: A CUDA-to-rCUDA Converter

Carlos Reano Gonzalez

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Tesla C1060, Tesla C2050, Thesis

March 9, 2013 by hgpu

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Chris J. Newburn, Rajiv Deodhar, Serguei Dmitriev, Ravi Murty, Ravi Narayanaswamy, John Wiegert, Francisco Chinchilla, Russell McGuire

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Tags: Compilers, Computer science, Heterogeneous systems, Intel, Intel Phi, Programming techniques

February 18, 2013 by hgpu

Effectiveness of program transformations and compilers for directive-based GPU programming models

Swapnil Avinash Ghike

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Optimization, Performance, Tesla X2090, Thesis

February 9, 2013 by hgpu

Portable Performance on Heterogeneous Architectures

Phitchaya Mangpo Phothilimthana, Jason Ansel, Jonathan Ragan-Kelley, Saman Amarasinghe

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Tags: Artificial intelligence, ATI, ATI Radeon HD 6630 M, Compilers, Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, OpenCL, Performance, Tesla C2070

February 2, 2013 by hgpu

A GPU Based Implementation of Side Effect Analysis

Sudhakar Sah, Vinay G. Vaidya

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 480

January 17, 2013 by hgpu

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Dominik Grewe, Zheng Wang, Michael F.P. O'Boyle

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Tags: ATI, ATI Radeon HD 7970, Compilers, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Programming Languages

January 8, 2013 by hgpu

KFusion: Obtaining Modularity and Performance with Regards to General Purpose GPU Computing and Co-processors

Liam Kiemele

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Source codes

Tags: Compilers, Computer science, nVidia, OpenCL, Package, Performance, Tesla C2075, Thesis

December 20, 2012 by hgpu

Multi-level Debugging for Multi-stage, Parallelizing Compilers

Richard Xia, Tayfun Elmas, Shoaib Ashraf Kamil, Armando Fox, Koushik Sen

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Tags: Compilers, Computer science, CUDA, nVidia, Package, Python

December 12, 2012 by hgpu

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

Tiark Rompf

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Software Engineering, Tesla C2050, Thesis

December 8, 2012 by hgpu

A MPI back-end for the OpenACC accULL. Exploiting OpenACC semantics in Message Passing Clusters

Juan Jose Fumero

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Tags: Algorithms, Compilers, Computer science, Heterogeneous systems, MPI, OpenACC, OpenCL

December 4, 2012 by hgpu

From Parallel Programs to Customized Parallel Processors

Pekka Jaaskelainen

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Tags: Algorithms, Compilers, Computer science, FPGA, High-level Languages, nVidia, nVidia GeForce 9400, OpenCL, Thesis

November 27, 2012 by hgpu

A Data-Parallel Algorithmic Modelica Extension for Efficient Execution on Multi-Core Platforms

Mahder Gebremedhin, Afshin Hemmati Moghadam, Peter Fritzson, Kristian Stavaker

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Tags: Algorithms, Benchmarking, Compilers, Computer science, Matrix multiplication, nVidia, OpenCL, Tesla M2050

November 27, 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

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high performance computing on graphics processing units: hgpu.org

CU2rCU: A CUDA-to-rCUDA Converter

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Effectiveness of program transformations and compilers for directive-based GPU programming models

Portable Performance on Heterogeneous Architectures

A GPU Based Implementation of Side Effect Analysis

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

KFusion: Obtaining Modularity and Performance with Regards to General Purpose GPU Computing and Co-processors

Multi-level Debugging for Multi-stage, Parallelizing Compilers

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

A MPI back-end for the OpenACC accULL. Exploiting OpenACC semantics in Message Passing Clusters

From Parallel Programs to Customized Parallel Processors

A Data-Parallel Algorithmic Modelica Extension for Efficient Execution on Multi-Core Platforms

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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