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GeNN: a code generation framework for accelerated brain simulations

Esin Yavuz, James Turner, Thomas Nowotny

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Tags: Biology, Code generation, CUDA, Neural networks, Neuroscience, Numerical simulation, nVidia, nVidia Quadro K 2000 M, Package, Tesla C2070, Tesla K40

January 29, 2016 by hgpu

A framework for efficient execution on GPU and CPU+GPU systems

Jean-Francois Dollinger

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Performance, Thesis

January 19, 2016 by hgpu

GRATER: An Approximation Workflow for Exploiting Data-Level Parallelism in FPGA Acceleration

Atieh Lotfi, Abbas Rahimi, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Rajesh K. Gupta

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Code generation, Computer science, FPGA, OpenCL

December 12, 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

MetaFork: A Compilation Framework for Concurrency Models Targeting Hardware Accelerators and Its Application to the Generation of Parametric CUDA Kernels

Changbo Chen, Xiaohui Chen, Abdoul-Kader Keita, Marc Moreno Maza, Ning Xie

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Tags: Code generation, Computer science, CUDA, nVidia, Package

October 18, 2015 by hgpu

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

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 OpenCL code generation for multi-device heterogeneous architectures

Pei Li, Elisabeth Brunet, Francois Trahay, Christian Parrot, Gael Thomas, Raymond Namyst

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Tags: Code generation, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia Quadro FX 5800, OpenCL

September 19, 2015 by hgpu

Source-to-Source Automatic Program Transformations for GPU-like Hardware Accelerators

Mehdi Amini

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Tags: ATI, ATI Radeon HD 6970, Code generation, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 670, OpenCL, Tesla C1060, Tesla C2070, Thesis

August 24, 2015 by hgpu

A Parallelizing Matlab Compiler Framework and Run time for Heterogeneous Systems

Sam Skalicky, Sonia Lopez, Marcin Lukowiak, Andrew G. Schmidt

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Tags: Code generation, Computer science, FPGA, Heterogeneous systems, Matlab

August 21, 2015 by hgpu

Runtime Code Generation and Data Management for Heterogeneous Computing in Java

Juan Jose Fumero, Toomas Remmelg, Michel Steuwer, Christophe Dubach

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Tags: AMD Radeon R9 295X2, ATI, Code generation, Computer science, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX Titan, OpenCL

August 18, 2015 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

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high performance computing on graphics processing units: hgpu.org

GeNN: a code generation framework for accelerated brain simulations

A framework for efficient execution on GPU and CPU+GPU systems

GRATER: An Approximation Workflow for Exploiting Data-Level Parallelism in FPGA Acceleration

Compiling and Optimizing Java 8 Programs for GPU Execution

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

MetaFork: A Compilation Framework for Concurrency Models Targeting Hardware Accelerators and Its Application to the Generation of Parametric CUDA Kernels

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

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

Automatic OpenCL code generation for multi-device heterogeneous architectures

Source-to-Source Automatic Program Transformations for GPU-like Hardware Accelerators

A Parallelizing Matlab Compiler Framework and Run time for Heterogeneous Systems

Runtime Code Generation and Data Management for Heterogeneous Computing in Java

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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