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Increasing programmability of an embedded domain specific language for GPGPU kernels using static analysis

Niklas Ulvinge

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Thesis

March 4, 2014 by hgpu

Automatic Resource-Constrained Static Task Parallelization

Dounia Khaldi

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Tags: Algorithms, Code generation, Computer science, MPI, OpenCL, Task scheduling, Thesis

January 28, 2014 by hgpu

High Performance Code Generation for Stencil Computation on Heterogeneous Multi-device Architectures

Pei Li, Elisabeth Brunet, Raymond Namyst

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Tags: Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 460, OpenCL

January 14, 2014 by hgpu

A Framework for Productive, Efficient and Portable Parallel Computing

Ekaterina I. Gonina

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Tags: Algorithms, Code generation, Computer science, CUDA, MapReduce, nVidia, nVidia GeForce GTX 480, Package, Python, Thesis

January 12, 2014 by hgpu

DEF-G: Declarative Framework for GPU Environment

Robert Senser, Tom Altman

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Tags: Code generation, Computer science, Filtering, nVidia, nVidia GeForce GT 430, OpenCL, Tesla T20

January 5, 2014 by hgpu

Multilayered Abstractions for Partial Differential Equations

Graham Robert Markall

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Code generation, CUDA, Differential equations, FEM, Finite element method, Mathematics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Partial differential equations, PDEs, Software Engineering, Thesis

December 11, 2013 by hgpu

A Methodology for Translating C-Programs to OpenCL

Krishnahari Thouti, S. R. Sathe

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia Quadro FX 3800, OpenCL, Programming Languages

November 16, 2013 by hgpu

SAGE: Self-Tuning Approximation for Graphics Engines

Mehrzad Samadi, Janghaeng Lee, D. Anoushe Jamshidi, Amir Hormati, Scott Mahlke

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Tags: Algorithms, Code generation, Compilers, CUDA, Image processing, Machine learning, nVidia, nVidia GeForce GTX 560, Performance

November 14, 2013 by hgpu

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Michal Januszewski, Marcin Kostur

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Tags: Code generation, Computational Physics, CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 285, OpenCL, Package, Physics, Python, Tesla C1060, Tesla C2050, Tesla K10, Tesla K20

November 12, 2013 by hgpu

Automatic Synthesis of Heterogeneous CPU-GPU Embedded Applications from a UML Profile

Federico Ciccozzi

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

November 8, 2013 by hgpu

Towards Code Generation from Design Models for Embedded Systems on Heterogeneous CPU-GPU Platforms

Federico Ciccozzi

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

October 18, 2013 by hgpu

Domain-Specific Languages for Heterogeneous Parallel Computing

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Hassan Chafi, Tiark Rompf, Martin Odersky, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Tesla C2050

October 15, 2013 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Increasing programmability of an embedded domain specific language for GPGPU kernels using static analysis

Automatic Resource-Constrained Static Task Parallelization

High Performance Code Generation for Stencil Computation on Heterogeneous Multi-device Architectures

A Framework for Productive, Efficient and Portable Parallel Computing

DEF-G: Declarative Framework for GPU Environment

Multilayered Abstractions for Partial Differential Equations

A Methodology for Translating C-Programs to OpenCL

SAGE: Self-Tuning Approximation for Graphics Engines

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Automatic Synthesis of Heterogeneous CPU-GPU Embedded Applications from a UML Profile

Towards Code Generation from Design Models for Embedded Systems on Heterogeneous CPU-GPU Platforms

Domain-Specific Languages for Heterogeneous Parallel Computing

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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