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Parallel source code transformation techniques using design patterns

David del Rio Astorga

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Tags: Algorithms, Auto-Tuning, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Tesla K40, Thesis

December 2, 2018 by hgpu

PanJoin: A Partition-based Adaptive Stream Join

Fei Pan, Hans-Arno Jacobsen

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Tags: Algorithms, Computer science, Databases, FPGA, OpenCL

December 2, 2018 by hgpu

Performance Portability Challenges for Fortran Applications

Abigail Hsu, David Neill Asanza, Joseph A. Schoonover, Zach Jibben, Neil N. Carlson, Robert Robey

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Tags: Computer science, CUDA, Finite difference, Fortran, nVidia, OpenMP, Package, performance portability, Tesla P100, Tesla V100

December 2, 2018 by hgpu

CLort: High Throughput and Low Energy Network Intrusion Detection on IoT Devices with Embedded GPUs

Charalampos Stylianopoulos, Linus Johansson, Oskar Olsson, Magnus Almgren

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Tags: ARM, Computer science, IoT, OpenCL, Package, Security

November 25, 2018 by hgpu

SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks

Linnan Wang, Wei Wu, Yiyang Zhao, Junyu Zhang, Hang Liu, George Bosilca, Jack Dongarra, Maurice Herlihy, Rodrigo Fonseca

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Tags: Compression, Computer science, CUDA, Deep learning, FFT, GPU cluster, Neural networks, nVidia, Package, Tesla P100

November 25, 2018 by hgpu

SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences

Enzo Rucci, Carlos Garcia, Guillermo Botella, Armando De Giusti, Marcelo Naiouf, Manuel Prieto-Matias

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Tags: Algorithms, Biology, FPGA, OpenCL, Package, Smith-Waterman algorithm

November 25, 2018 by hgpu

Modeling Deep Learning Accelerator Enabled GPUs

Md Aamir Raihan, Negar Goli, Tor Aamodt

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Tags: Computer science, CUDA, Deep learning, Hardware Architecture, Machine learning, nVidia, Tesla V100

November 25, 2018 by hgpu

Dense and sparse parallel linear algebra algorithms on graphics processing units

Alejandro Lamas Davina

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, MPI, nVidia, Sparse, Tesla K20, Tesla M2090, Thesis

November 25, 2018 by hgpu

Accelerating Low-End Edge Computing with Cross-Kernel Functionality Abstraction

Chao Wu, Yaoxue Zhang, Yuezhi Zhou, Qiushi Li

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Performance

November 18, 2018 by hgpu

Spatter: A Benchmark Suite for Evaluating Sparse Access Patterns

Patrick Lavin, Jason Riedy, Rich Vuduc, Jeffrey Young

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Tags: Benchmarking, Computer science, CUDA, FPGA, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan XP, OpenCL, Package, Performance, Tesla P100

November 18, 2018 by hgpu

FusionStitching: Deep Fusion and Code Generation for Tensorflow Computations on GPUs

Guoping Long, Jun Yang, Kai Zhu, Wei Lin

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Tags: Code generation, Computer science, CUDA, Deep learning, Machine learning, nVidia, TensorFlow

November 18, 2018 by hgpu

StePS: A Multi-GPU Cosmological N-body Code for Compactified Simulations

Gabor Racz, Istvan Szapudi, Laszlo Dobos, Istvan Csabai, Alexander S. Szalay

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Tags: Astrophysics, Cosmology, CUDA, MPI, N-body simulation, nVidia, OpenMP, Package, Tesla K80

November 18, 2018 by hgpu

GPGPU Verification of Radix Sort

Let’s sort this out: GPGPU Verification of Radix Sort

EASYPAP: a Framework for Learning Parallel Programming

EASYPAP: a Framework for Learning Parallel Programming

LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment

LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment

StarNEig: A Task-based Library for Solving Nonsymmetric Eigenvalue Problems

Task-based, GPU-accelerated and Robust Library for Solving Dense Nonsymmetric Eigenvalue Problems

FLAMEGPU: a high performance GPU extension to the FLAME framework

Working With Incremental Spatial Data During Parallel (GPU) Computation

CommAnalyzer

Automated Runtime Analysis and Adaptation for Scalable Heterogeneous Computing

elevate: implementation of the Elevate language

A Language for Describing Optimization Strategies

reproducibility of TensorFlow with ResNet

Non-Determinism in TensorFlow ResNets

SCHNAPS

Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

Interoperable GPU Kernels as Latency Improver for MEC

Interoperable GPU Kernels as Latency Improver for MEC

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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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