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A Framework for Lattice QCD Calculations on GPUs

F. T. Winter, M. A. Clark, R. G. Edwards, B. Joo

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Tags: Algorithms, Code generation, Computational Physics, CUDA, High Energy Physics - Lattice, Mathematical Software, nVidia, Physics, PTX, QCD, Tesla K20

August 27, 2014 by hgpu

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Moritz Schmid, Oliver Reiche, Christian Schmitt, Frank Hannig, Jurgen Teich

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Tags: ARM, Code generation, Compilers, Computational Complexity, Computer science, Differential equations, FPGA, Image processing, Partial differential equations, PDEs

August 23, 2014 by hgpu

Optimising Purely Functional GPU Programs (Thesis)

Trevor L. McDonell

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Performance, Tesla T10, Thesis

August 10, 2014 by hgpu

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Albert Saa-Garriga, David Castells-Rufas, Jordi Carrabina

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2075, Tesla K20, Tesla M2050

July 28, 2014 by hgpu

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Esin Yavuz, James Turner, Thomas Nowotny

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Tags: Bioinformatics, Biology, Code generation, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C2070

July 28, 2014 by hgpu

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

Istvan Zoltan Reguly

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Tags: Algorithms, Code generation, Computer science, CUDA, Differential equations, FEM, Finite element method, Finite volume method, Fluid dynamics, Heterogeneous systems, Linear Algebra, nVidia, Partial differential equations, PDEs, Programming techniques, Tesla C2070, Tesla K20, Tesla K40, Thesis

July 24, 2014 by hgpu

Loo.py: transformation-based code generation for GPUs and CPUs

Andreas Klockner

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Tags: ATI, ATI Radeon HD 7990, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, Programming Languages, PyOpenCL, Python

June 2, 2014 by hgpu

Geometric Algebra Enhanced Precompiler for C++, OpenCL and Mathematica’s OpenCLLink

Patrick Charrier, Mariusz Klimek, Christian Steinmetz, Dietmar Hildenbrand

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

May 12, 2014 by hgpu

Piko: A Design Framework for Programmable Graphics Pipelines

Anjul Patney, Stanley Tzeng, Kerry A. Seitz Jr., John D. Owens

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Tags: 3D Graphics and Realism, Code generation, Computer science, nVidia, nVidia GeForce GTX 680, OpenCL, PTX, Rasterization, Raytracing, Rendering

April 29, 2014 by hgpu

An Automated Tool for Converting Directive Based C Code Into Parallel CUDA Code

Batliwala Saifuddin, Kadtan Lalit, Khan Mujjammil, Khandagale Pratik, S. M. Walunj

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Tags: Code generation, Computer science, CUDA, nVidia

April 19, 2014 by hgpu

Code Generation for Embedded Heterogeneous Architectures on Android

R. Membarth, O. Reiche, F. Hannig, J. Teich

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Tags: Code generation, Heterogeneous systems, Image processing

April 1, 2014 by hgpu

On-Demand Source Code Generation & Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K.A. Hawick, D.P.Playne

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

March 4, 2014 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

A Framework for Lattice QCD Calculations on GPUs

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Optimising Purely Functional GPU Programs (Thesis)

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

Loo.py: transformation-based code generation for GPUs and CPUs

Geometric Algebra Enhanced Precompiler for C++, OpenCL and Mathematica’s OpenCLLink

Piko: A Design Framework for Programmable Graphics Pipelines

An Automated Tool for Converting Directive Based C Code Into Parallel CUDA Code

Code Generation for Embedded Heterogeneous Architectures on Android

On-Demand Source Code Generation & Scheduling Optimised Parallel Applications on Heterogeneous Platforms

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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