high performance computing on graphics processing units: hgpu.org

hgpu.org » Code generation

Speculative Execution of Parallel Programs with Precise Exception Semantics on GPUs

Akihiro Hayashi, Max Grossman, Jisheng Zhao, Jun Shirako, Vivek Sarkar

View

Download (PDF)

Tags: Code generation, Computer science, Java, nVidia, OpenCL, Tesla M2050

October 5, 2013 by hgpu

Parametric GPU Code Generation for Affine Loop Programs

Athanasios Konstantinidis, Paul H. J. Kelly, J. Ramanujam, P. Sadayappan

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 580, OpenCL, Package, Tesla K20, Tesla M2070

October 5, 2013 by hgpu

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Jun Liu

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, nVidia, Tesla C2050, Thesis

October 3, 2013 by hgpu

Kokkos: Enabling performance portability across manycore architectures

H. Carter Edwards, Christian R. Trott

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, Intel Phi, Molecular dynamics, nVidia, Package, Tesla K20

September 17, 2013 by hgpu

Automatic Skeleton-Based Compilation through Integration with an Algorithm Classification

Cedric Nugteren, Pieter Custers, Henk Corporaal

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, OpenCL, OpenMP

August 7, 2013 by hgpu

The Promises of Hybrid Hexagonal/Classical Tiling for GPU

Tobias Grosser, Sven Verdoolaege, Albert Cohen, P. Sadayappan

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia Quadro NVS 5200 M, PTX

July 31, 2013 by hgpu

Counting and Occurrence Sort for GPUs using an Embedded Language

Josef Svenningsson, Bo Joel Svensson, Mary Sheeran

View

Download (PDF)

Source codes

Tags: Algorithms, Code generation, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 670, Package, Sorting

July 30, 2013 by hgpu

From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation

Marek Blazewicz, Ian Hinder, David M. Koppelman, Steven R. Brandt, Milosz Ciznicki, Michal Kierzynka, Frank Loffler, Erik Schnetter, Jian Tao

View

Download (PDF)

Tags: Code generation, Computational Physics, CUDA, Differential equations, Finite difference, MPI, nVidia, OpenMP, Partial differential equations, PDEs, Physics, Tesla M2050

July 25, 2013 by hgpu

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Dmitry Mikushin, Nikolay Likhogrud, Eddy Zheng Zhang, Christopher Bergstrom

View

Download (PDF)

Source codes

Tags: Code generation, Compilers, Computer science, CUDA, Fortran, nVidia, OpenACC, Package, PTX, Tesla K20

July 15, 2013 by hgpu

Scalable Techniques for Scheduling and Mapping DSP Applications onto Embedded Multiprocessor Platforms

George Zaki

View

Download (PDF)

Tags: Algorithms, Code generation, Computational Engineering, CUDA, Data parallelism, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, Signal processing, Thesis

July 12, 2013 by hgpu

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Roshan Dathathri, Chandan Reddy, Thejas Ramashekar, Uday Bondhugula

View

Download (PDF)

Tags: ATI, ATI FirePro V4800, ATI Radeon HD 6550, Code generation, Computer science, Heterogeneous systems, nVidia, Tesla C2050

July 1, 2013 by hgpu

Exploiting multi-level parallelism in streaming applications for heterogeneous platforms with GPUs

Ana Balevic

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Tesla C2050, Thesis

July 1, 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

* * *

high performance computing on graphics processing units: hgpu.org

Speculative Execution of Parallel Programs with Precise Exception Semantics on GPUs

Parametric GPU Code Generation for Affine Loop Programs

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Kokkos: Enabling performance portability across manycore architectures

Automatic Skeleton-Based Compilation through Integration with an Algorithm Classification

The Promises of Hybrid Hexagonal/Classical Tiling for GPU

Counting and Occurrence Sort for GPUs using an Embedded Language

From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Scalable Techniques for Scheduling and Mapping DSP Applications onto Embedded Multiprocessor Platforms

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Exploiting multi-level parallelism in streaming applications for heterogeneous platforms with GPUs

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

Most viewed papers (last 30 days)