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Compiler Fuzzing through Deep Learning

Chris Cummins, Pavlos Petoumenos, Hugh Leather, Alastair Murray

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Tags: Compilers, Computer science, Deep learning, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 780, OpenCL, Package

July 1, 2018 by hgpu

DeepSmith: Compiler Fuzzing through Deep Learning

Chris Cummins, Pavlos Petoumenos, Alastair Murray, Hugh Leather

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Tags: Compilers, Computer science, Deep learning, nVidia, OpenCL, Package, Tesla K40

June 24, 2018 by hgpu

Glow: Graph Lowering Compiler Techniques for Neural Networks

Nadav Rotem, Jordan Fix, Saleem Abdulrasool, Summer Deng, Roman Dzhabarov, James Hegeman, Roman Levenstein, Bert Maher, Satish Nadathur, Jakob Olesen, Jongsoo Park, Artem Rakhov, Misha Smelyanskiy

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Tags: Code generation, Compilers, Computer science, CUDA, Deep learning, Heterogeneous systems, Linear Algebra, Machine learning, Neural networks, nVidia, Package

May 20, 2018 by hgpu

MACC: An OpenACC Transpiler for Automatic Multi-GPU Use

Kazuaki Matsumura, Mitsuhisa Sato, Taisuke Boku, Artur Podobas, Satoshi Matsuoka

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Tags: Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla P100

March 22, 2018 by hgpu

Technical Report about Tiramisu: a Three-Layered Abstraction for Hiding Hardware Complexity from DSL Compilers

Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane, Emanuele Del Sozzo, Patricia Suriana, Shoaib Kamil, Saman Amarasinghe

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Tags: Compilers, Computer science, DSL, FPGA, Matrix multiplication, nVidia, OpenMPI, Performance, Programming Languages, PTX, Tesla K40

March 3, 2018 by hgpu

SkePU 2: Flexible and Type-Safe Skeleton Programming for Heterogeneous Parallel Systems

August Ernstsson, Christoph Kessler

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, OpenMP, Package, Tesla K20

January 28, 2018 by hgpu

A Survey on Compiler Autotuning using Machine Learning

Amir H. Ashouri, William Killian, John Cavazos, Gianluca Palermo, Cristina Silvano

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Tags: Auto-Tuning, Compilers, Computer science, Machine learning, Performance

January 28, 2018 by hgpu

ImageCL: Language and source-to-source compiler for performance portability, load balancing, and scalability prediction on heterogeneous systems

Thomas L. Falch, Anne C. Elster

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Tags: ATI, ATI Radeon HD 7970, Compilers, Heterogeneous systems, Image processing, Machine learning, nVidia, nVidia GeForce GTX 960, OpenCL, Package, performance portability, Tesla K40

January 13, 2018 by hgpu

High Performance Stencil Code Generation with Lift

Bastian Hagedorn, Larisa Stoltzfus, Michel Steuwer, Sergei Gorlatch, Christophe Dubach

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Tags: ARM, ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Linear Algebra, nVidia, OpenCL, Package, performance portability, Scala, Tesla K20

January 13, 2018 by hgpu

Efficient Target and Application Specific Selection and Ordering of Compiler Passes

Ricardo Jorge Ferreira Nobre

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Tags: Code generation, Compilers, Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 460, nVidia GeForce GTX 480, OpenCL, PTX, Thesis

November 26, 2017 by hgpu

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Marcio M. Pereira, Rafael C. F. Sousa, Guido Araujo

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Tags: ARM, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, LLVM, nVidia, OpenCL, OpenMP, Package, Tesla K40

November 21, 2017 by hgpu

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Wim Vanderbauwhede, Gavin Davidson

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Tags: Compilers, Computer science, Fortran, Heterogeneous systems, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Package

November 16, 2017 by hgpu

Programming Your GPU with OpenMP: A Hands-On Introduction

Evaluating the performance of HPC-style SYCL applications

sycl-bench: SYCL Benchmark Suite

SYCL-Bench: A Versatile Single-Source Benchmark Suite for Heterogeneous Computing

BlaBla: A Python package for clinical linguistic feature extraction in multiple languages

BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages

gocudnn: Go Bindings for cudnn and other cuda pacakges

Deep Learning with GO

Task-Based Parallel Strategies for CFD Application in Heterogeneous CPU/GPU Resources

DALI: a library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications

Importance of Data Loading Pipeline in Training Deep Neural Networks

AutoParBench: a benchmark framework to evaluate compilers and tools designed to automatically insert OpenMP directives

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

cuda-kat: The CUDA Kernel Author's Toolkit

cuda-kat: The CUDA Kernel Author’s Toolkit

GEVO: GPU Code Optimization using Evolutionary Computation

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Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

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13-15

Boston, USA

7th International Workshop on OpenCL, 2019

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Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

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26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

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high performance computing on graphics processing units: hgpu.org

Compiler Fuzzing through Deep Learning

DeepSmith: Compiler Fuzzing through Deep Learning

Glow: Graph Lowering Compiler Techniques for Neural Networks

MACC: An OpenACC Transpiler for Automatic Multi-GPU Use

Technical Report about Tiramisu: a Three-Layered Abstraction for Hiding Hardware Complexity from DSL Compilers

SkePU 2: Flexible and Type-Safe Skeleton Programming for Heterogeneous Parallel Systems

A Survey on Compiler Autotuning using Machine Learning

ImageCL: Language and source-to-source compiler for performance portability, load balancing, and scalability prediction on heterogeneous systems

High Performance Stencil Code Generation with Lift

Efficient Target and Application Specific Selection and Ordering of Compiler Passes

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Recent source codes

Programming Your GPU with OpenMP: A Hands-On Introduction

sycl-bench: SYCL Benchmark Suite

BlaBla: A Python package for clinical linguistic feature extraction in multiple languages

gocudnn: Go Bindings for cudnn and other cuda pacakges

Task-Based Parallel Strategies for CFD Application in Heterogeneous CPU/GPU Resources

DALI: a library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications

AutoParBench: a benchmark framework to evaluate compilers and tools designed to automatically insert OpenMP directives

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

cuda-kat: The CUDA Kernel Author's Toolkit

GEVO: GPU Code Optimization using Evolutionary Computation

Most viewed papers (last 30 days)

Featured events

8th International Workshop on OpenCL, including SYCLCon, 2019

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019