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Tesla vs. Xeon Phi vs. Radeon A Compiler Writer’s Perspective

Brent Leback, Douglas Miles, Michael Wolfe

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Tags: ATI, Compilers, Computer science, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla

December 18, 2013 by hgpu

Integrating Multi-GPU Execution in an OpenACC Compiler

Toshiya Komoda, Shinobu Miwa, Hiroshi Nakamura, Naoya Maruyama

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Tags: Compilers, Computer science, CUDA, MPI, nVidia, OpenACC, Tesla C2075, Tesla M2050

November 18, 2013 by hgpu

A Methodology for Translating C-Programs to OpenCL

Krishnahari Thouti, S. R. Sathe

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia Quadro FX 3800, OpenCL, Programming Languages

November 16, 2013 by hgpu

SAGE: Self-Tuning Approximation for Graphics Engines

Mehrzad Samadi, Janghaeng Lee, D. Anoushe Jamshidi, Amir Hormati, Scott Mahlke

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Tags: Algorithms, Code generation, Compilers, CUDA, Image processing, Machine learning, nVidia, nVidia GeForce GTX 560, Performance

November 14, 2013 by hgpu

Characterizing the Challenges and Evaluating the Efficacy of a CUDA-to-OpenCL Translator

Mark Gardner, Paul Sathre, Wu-chun Feng, Gabriel Martinez

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL

October 13, 2013 by hgpu

Dandelion: a Compiler and Runtime for Heterogeneous Systems

Christopher J. Rossbach, Yuan Yu, Jon Currey, Jean-Philippe Martin, Dennis Fetterly

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20

October 12, 2013 by hgpu

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Jun Liu

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

October 3, 2013 by hgpu

Separate Compilation in a Language-Integrated Heterogeneous Environment

Mike Murphy, Jaydeep Marathe, Girish Bharambe, Sean Lee, Vinod Grover

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia

September 29, 2013 by hgpu

Compilation techniques and language support to facilitate dependence-driven computation

Albert Sidelnik

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Thesis

August 27, 2013 by hgpu

General Transformations for GPU Execution of Tree Traversals

Michael Goldfarb, Youngjoon Jo, Milind Kulkarni

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Tags: Algorithms, Compilers, Computer science, CUDA, KD-tree, nVidia, Performance, Tesla C2070

August 15, 2013 by hgpu

Compiler-based Data Prefetching and Streaming Non-temporal Store Generation for the Intel Xeon Phi Coprocessor

Rakesh Krishnaiyer, Emre Kultursay, Pankaj Chawla, Serguei Preis, Anatoly Zvezdin, Hideki Saito

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Tags: Compilers, Computer science, Intel, Intel Phi, Prefetch

August 8, 2013 by hgpu

Automatic Skeleton-Based Compilation through Integration with an Algorithm Classification

Cedric Nugteren, Pieter Custers, Henk Corporaal

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

August 7, 2013 by hgpu

PyTorch: An Imperative Style, High-Performance Deep Learning Library

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Masivo: Parallel public transport routes simulation

Masivo: Parallel Simulation Model Based on OpenCL for Massive Public Transportation Systems’ Routes

FBLAS: BLAS implementation for Intel FPGA

FBLAS: Streaming Linear Algebra Kernels on FPGA

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things

Titan: A CUDA-based physics simulation sandbox for high-performance robotics, physics, and reinforcement learning applications

Titan: A Parallel Asynchronous Library for Multi-Agent and Soft-Body Robotics using NVIDIA CUDA

onYourMarks: A deep learning benchmark implementation for Nvidia's Jetson TX2

Benchmarking Deep Learning Models on Jetson TX2

Hacking Neural Networks: A small course on exploiting and defending neural networks

Hacking Neural Networks: A Short Introduction

A Computing Kernel for Network Binarization on PyTorch

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

Framework for Parallel Kernels Auto-tuning

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2020

April

27-29

Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

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

2019

May

14

Larnaca, Cyprus

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

2019

July

26-28

Rome, Italy

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

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