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Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Nuno Fachada, Agostinho C. Rosa

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Tags: Agent-based modeling, AMD, cpu, Intel, OpenCL, simulation

July 24, 2019 by fakenmc

Automated Testing of Graphics Shader Compilers

Alastair F. Donaldson, Hugues Evrard, Andrei Lascu, Paul Thomson

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Tags: AMD Radeon R9 Fury, ARM, ATI, ATI Radeon HD 7700, Compilers, Computer science, GLSL, Intel, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan X, OpenGL, Rendering, Security, Shaders, WebGL

September 21, 2017 by hgpu

Input Space Splitting for OpenCL

Simon Moll, Johannes Doerfert, Sebastian Hack

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Tags: Compilers, Computer science, Intel, LLVM, OpenCL

March 5, 2016 by hgpu

A Survey of Architectural Techniques For Improving Cache Power Efficiency

Sparsh Mittal

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Tags: Architecture, cache, cpu, Energy-efficient computing, GPU, Intel, Memory, Power-efficient computing

January 19, 2015 by sparsh0mittal

Preliminary Experiments with XKaapi on Intel Xeon Phi Coprocessor

Joao Vicente Ferreira Lima, Francois Broquedis, Thierry Gautier, Bruno Raffin

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Tags: Computer science, Factorization, Intel, Intel Phi, Intel Xeon Phi

November 11, 2013 by hgpu

Understanding the Costs of Many-Task Computing Workloads on Intel Xeon Phi Coprocessors

Jeffrey Johnson, Scott J. Krieder, Benjamin Grimmer, Justin M. Wozniaky, Michael Wildeyz, Ioan Raicu

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Tags: Computer science, Heterogeneous systems, Intel, Intel Phi

October 21, 2013 by hgpu

OpenCL Task Partitioning in the Presence of GPU Contention

Dominik Grewe, Zheng Wang, and Michael F.P. O'Boyle

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Tags: Computer science, Heterogeneous systems, Intel, Intel HD Graphics 4000, Machine learning, OpenCL, Task scheduling

September 25, 2013 by hgpu

Performance Evaluation of Intel Xeon Phi Coprocessor using XKaapi

Joao V. F. Lima, Nicolas Maillard, Franciois Broquedis, Thierry Gautier, Bruno Raffin

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Tags: Benchmarking, Computer science, Intel, Intel Phi, Performance

August 26, 2013 by hgpu

First experiences with the Intel MIC architecture at LRZ

Volker Weinberg, Momme Allalen

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Tags: Computer science, Intel, Intel Phi, OpenMP, Performance

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

Lattice QCD on Intel Xeon Phi

Balint Joo, Dhiraj D. Kalamkar, Karthikeyan Vaidyanathan, Mikhail Smelyanskiy, Kiran Pamnany, Victor W Lee, Pradeep Dubey, William Watson III

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Tags: CUDA, High Energy Physics - Lattice, Intel, Intel Phi, nVidia, Physics, QCD, Tesla K20

July 20, 2013 by hgpu

Benchmarking Intel Xeon Phi to Guide Kernel Design

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips, Lilun Zhang, Yonggang Che, Chuanfu Xu

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Tags: Benchmarking, Computer science, Intel, Intel Phi, Performance

July 14, 2013 by hgpu

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Learnergy: a Python library for energy-based machine learning models

Learnergy: Energy-based Machine Learners

Towards automated kernel selection in machine learning systems: A SYCL case study

Towards automated kernel selection in machine learning systems: A SYCL case study

CLFuzz

Automated test generation for OpenCL kernels using fuzzing and constraint solving

High-Performance Graph Primitives on GPUs

Fast Gunrock Subgraph Matching (GSM) on GPUs

Inline Vector Compression for Computational Physics

Inline Vector Compression for Computational Physics

AvA: Automatic virtualization of (general) accelerators

AvA: Accelerated Virtualization of Accelerators

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

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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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