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Scalable Applications on Heterogeneous System Architectures: A Systematic Performance Analysis Framework

Robert Dietrich

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Tags: Computer science, CUDA, Data acquisition, Heterogeneous systems, MPI, nVidia, OpenACC, OpenCL, Tesla K80, Tesla V100, Thesis

December 1, 2019 by hgpu

Parallelizing Multiple Flow Accumulation Algorithm using CUDA and OpenACC

Natalija Stojanovic, Dragan Stojanovic

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenACC, Package, Tesla K80

September 15, 2019 by hgpu

An optimizing multi-platform source-to-source compiler framework for the NEURON MODeling Language

Pramod Kumbhar, Omar Awile, Liam Keegan, Jorge Blanco Alonso, James King, Michael Hines, Felix Schuermann

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Tags: Biophysics, Code generation, Compilers, Computer science, CUDA, HPC, Intel Xeon Phi, LLVM, nVidia, OpenACC, OpenMP, Package

May 15, 2019 by hgpu

Loop Perforation in OpenACC

Ahmad Lashgar, Ehsan Atoofian, Amirali Baniasadi

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Tags: Computer science, CUDA, OpenACC, OpenCL, Package, Performance

April 20, 2019 by hgpu

Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation

Ada Sedova, Andreas Tillack, Arnold Tharrington

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Tags: Chemistry, Molecular dynamics, Molecular simulation, nVidia, OpenACC, performance portability, Physics, Tesla K20

March 3, 2019 by hgpu

Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes

Emanuele Vitali, Davide Gadioli, Gianluca Palermo, Andrea Beccari, Carlo Cavazzoni, Cristina Silvano

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, molecular docking, MPI, nVidia, OpenACC, OpenMP, Tesla K80

January 27, 2019 by hgpu

Towards Automatic Transformation of Legacy Scientific Code into OpenCL for Optimal Performance on FPGAs

Wim Vanderbauwhede, Syed Waqar Nabi

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Tags: Compilers, Computer science, Fortran, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenACC, OpenCL, OpenMP, Package

January 6, 2019 by hgpu

Deep Learning by Doing: The NVIDIA Deep Learning Institute and University Ambassador Program

Xi Chen, Gregory S. Gutmann, Joe Bungo

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Tags: Cloud, Computer science, CUDA, Deep learning, Distributed computing, Education, Neural networks, nVidia, OpenACC

December 23, 2018 by hgpu

Clacc: Translating OpenACC to OpenMP in Clang

Joel E. Denny, Seyong Lee, Jeffrey S. Vetter

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Tags: Compilers, Computer science, Heterogeneous systems, LLVM, nVidia, nVidia GeForce GTX 1050, OpenACC, OpenMP

December 9, 2018 by hgpu

Evaluating Performance Portability of Accelerator Programming Models using SPEC ACCEL 1.2 Benchmarks

Swen Boehm, Swaroop Pophale, Veronica G. Vergara Larrea, Oscar Hernandez

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Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenACC, OpenCL, OpenMP, performance portability, Tesla K20, Tesla V100

September 23, 2018 by hgpu

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Jacob Lambert, Seyong Lee, Jungwon Kim, Jeffrey S. Vetter, Allen D. Malony

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Tags: Computer science, FPGA, nVidia, OpenACC, OpenCL, Tesla K40

July 1, 2018 by hgpu

Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

Qiang Liu, Yi Qin, Guodong Li

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Tags: Benchmarking, Earth and Space Sciences, Numerical simulation, nVidia, OpenACC, Tesla K20

May 5, 2018 by hgpu

SolidTextureNets

On Demand Solid Texture Synthesis Using Deep 3D Networks

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

deepnetts: Deep Netts Pure Java Deep Learning Engine

Towards High Performance Java-based Deep Learning Frameworks

PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite

A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs

TACO: The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs

A Unified Iteration Space Transformation Framework for Sparse and Dense Tensor Algebra

OpenCL-FPGA-LLVM: LLVM-based automation of memory decoupling for OpenCL applications on FPGAs

LLVM-based automation of memory decoupling for OpenCL applications on FPGAs

CUDAnative.jl: Julia support for native CUDA programming

Abstractions for Programming Graphics Processors in High-Level Programming Languages

GPU explicit-state model checking

Porting tree-based hash table compression to GPGPU model checking

OCLADock: OpenCL Accelerated Molecular Docking

Accelerating Molecular Docking by Parallelized Heterogeneous Computing – A Case Study of Performance, Quality of Results, and Energy-Efficiency using CPUs, GPUs, and FPGAs

jax-md: Differentiable, Hardware Accelerated, Molecular Dynamics

JAX, M.D.: End-to-End Differentiable, Hardware Accelerated, Molecular Dynamics in Pure Python

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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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