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A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

Rahul Garg

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Tags: AMD Radeon HD 8650, ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Computer science, Intel HD Graphics 4000, Matlab, Matrix multiplication, nVidia, nVidia GeForce GT 650 M, OpenCL, Package, Python, Tesla C2050, Thesis

October 6, 2015 by hgpu

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high performance computing on graphics processing units: hgpu.org

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

Recent source codes

MECCA development in accelerators - KPP Fortran to CUDA source-to-source pre-processor

Internally-maintained tool for examining GPU scheduling behavior

CLBlast: Tuned OpenCL BLAS

Open source implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning

IDA*

Repository for 1D Swept rule scheme written in CUDA C

DeepMetabolism: a deep learning algorithm to predict phenotype from genome sequencing

OpenDwarfs

parallel-si: Efficient Parallel Strategy Improvement for Parity Games

AVX-512 sort functions

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Featured events

4th International Conference on Biomedical and Bioinformatics Engineering (ICBBE), 2017

9th International Conference on Signal Processing Systems (ICSPS), 2017

The 5th International conference on Control, Mechatronics and Automation (ICCMA), 2017

8th International Conference on Biology, Environment and Chemistry (ICBEC), 2017

2nd International Conference on Communication and Information Systems (ICCIS), 2017