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Performance Portable GPU Code Generation for Matrix Multiplication

Toomas Remmelg, Thibaut Lutz, Michel Steuwer, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Matrix multiplication, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX Titan Black, OpenCL

February 10, 2016 by hgpu

Bridging OpenCL and CUDA: A Comparative Analysis and Translation

Junghyun Kim, Thanh Tuan Dao, Jaehoon Jung, Jinyoung Joo, Jaejin Lee

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Tags: ATI, ATI Radeon HD 7970, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL

December 1, 2015 by hgpu

Free Launch: Optimizing GPU Dynamic Kernel Launches through Thread Reuse

Guoyang Chen, Xipeng Shen

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Tags: Compilers, Computer science, CUDA, nVidia, Tesla K20, Tesla K40

November 8, 2015 by hgpu

CLOP: A Multi-stage Compiler to Seamlessly Embed Heterogeneous Code

Dmitri Makarov, Matthias Hauswirth

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Source codes

Tags: Compilers, Computer science, OpenCL, Package

October 29, 2015 by hgpu

Compiling and Optimizing Java 8 Programs for GPU Execution

Kazuaki Ishizaki, Akihiro Hayashi, Gita Koblents, Vivek Sarkar

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Tags: Code generation, Compilers, Computer science, CUDA, Java, nVidia, OpenCL, Tesla K40

October 27, 2015 by ahayashi

Machine-Learning-based Performance Heuristics for Runtime CPU/GPU Selection

Akihiro Hayashi, Kazuaki Ishizaki, Vivek Sarkar, Gita Koblents

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Tags: Code generation, Compilers, Computer science, CUDA, Java, Machine learning, nVidia, OpenCL, Tesla K40

October 27, 2015 by ahayashi

A Co-Design Framework with OpenCL Support for Low-Energy Wide SIMD Processor

Dongrui She, Yifan He, Luc Waeijen, Henk Corporaal

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Tags: Code generation, Compilers, Computer science, Embedded high-performance computing, OpenCL

September 24, 2015 by hgpu

Automatic Optimization of Thread Mapping for a GPGPU Programming Framework

Kazuhiko Ohno, Tomoharu Kamiya, Takanori Maruyama, Masaki Matsumoto

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Tags: Benchmarking, Compilers, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 980

July 15, 2015 by hgpu

Many-Core Compiler Fuzzing

Christopher Lidbury, Andrei Lascu, Nathan Chong, Alastair F. Donaldson

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Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Compilers, Computer science, FPGA, Intel HD 4600, Intel Xeon Phi, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan, OpenCL, Tesla K40, Tesla M2050

July 10, 2015 by hgpu

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Unnikrishnan C, Y N Srikant, Rupesh Nasre

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Tags: Compilers, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, OpenMP, Tesla C2050, Tesla C2075, Tesla K20

June 16, 2015 by hgpu

OMP2HMPP: Compiler Framework for Energy-Performance Trade-off Analysis of Automatically Generated Codes

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

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Tesla M2050

May 5, 2015 by hgpu

Generating Performance Portable Code using Rewrite Rules: From High-level Functional Expressions to High-Performance OpenCL Code

Michel Steuwer, Christian Fensch, Sam Lindley, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL

March 8, 2015 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Performance Portable GPU Code Generation for Matrix Multiplication

Bridging OpenCL and CUDA: A Comparative Analysis and Translation

Free Launch: Optimizing GPU Dynamic Kernel Launches through Thread Reuse

CLOP: A Multi-stage Compiler to Seamlessly Embed Heterogeneous Code

Compiling and Optimizing Java 8 Programs for GPU Execution

Machine-Learning-based Performance Heuristics for Runtime CPU/GPU Selection

A Co-Design Framework with OpenCL Support for Low-Energy Wide SIMD Processor

Automatic Optimization of Thread Mapping for a GPGPU Programming Framework

Many-Core Compiler Fuzzing

Falcon: A Graph Manipulation Language for Heterogeneous Systems

OMP2HMPP: Compiler Framework for Energy-Performance Trade-off Analysis of Automatically Generated Codes

Generating Performance Portable Code using Rewrite Rules: From High-level Functional Expressions to High-Performance OpenCL Code

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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