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Energy Efficient Computing on Multi-core Processors: Vectorization and Compression Techniques

Abdullah Al Hasib

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Tags: Compression, Computer science, Data parallelism, Intel Xeon Phi, Prefetch, Programming techniques, Thesis

June 20, 2018 by hgpu

Software Prefetching for Indirect Memory Accesses

Sam Ainsworth, Timothy M. Jones

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Tags: ARM, Benchmarking, Compilers, Computer science, Intel Xeon Phi, LLVM, MPI, Package, Prefetch

January 10, 2017 by hgpu

UNICORN: A Bulk Synchronous Programming Model, Framework and Runtime for Hybrid CPU-GPU Clusters

Tarun Beri

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Tags: Computer science, CUDA, FFT, GPU cluster, Linear Algebra, Matrix multiplication, nVidia, Package, Prefetch, Tesla M2070, Thesis

November 5, 2016 by hgpu

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Andreas Klockner, Lucas C. Wilcox, T. Warburton

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Code generation, Computer science, Fortran, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, Prefetch, Programming Languages, Python, Tesla K40

April 29, 2016 by hgpu

Breadth First Search Vectorization on the Intel Xeon Phi

Mireya Paredes, Graham Riley, Mikel Lujan

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Tags: Algorithms, Computer science, Databases, Intel Xeon Phi, Prefetch

April 14, 2016 by hgpu

Unlocking Bandwidth for GPUs in CC-NUMA Systems

Neha Agarwal, David Nellans, Mike O'Connor, Stephen W. Keckler, Thomas F. Wenisch

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Prefetch

February 6, 2015 by hgpu

Supporting Applications Involving Dynamic Data Structures and Irregular Memory Access on Emerging Parallel Platforms

Bin Ren

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Tags: Algorithms, Computer science, CUDA, Intel Xeon Phi, Memory model, nVidia, nVidia Quadro FX 5800, Prefetch, Tesla C2050, Thesis

September 19, 2014 by hgpu

Dynamic Data Management Among Multiple Databases for Optimization of Parallel Computations in Heterogeneous HPC Systems

Pawel Rosciszewski

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Tags: Computer science, Databases, Heterogeneous systems, nVidia, nVidia Quadro FX 3800, OpenCL, Prefetch, Tesla C2050

July 30, 2014 by hgpu

Performance-efficient mechanisms for managing irregularity in throughput processors

Minsoo Rhu

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Prefetch, Thesis

July 20, 2014 by hgpu

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

A Locality-Aware Memory Hierarchy for Energy-Efficient GPU Architectures

Minsoo Rhu, Michael Sullivan, Jingwen Leng, Mattan Erez

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Tags: Computer science, GPGPU-sim, Memory, Performance, Prefetch

October 29, 2013 by hgpu

APOGEE: adaptive prefetching on GPUs for energy efficiency

Ankit Sethia, Ganesh Dasika, Mehrzad Samadi, Scott Mahlke

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, OpenGL, Prefetch

September 28, 2013 by hgpu

OpenDwarfs: a benchmark suite consisting of different computation/communication idioms

Exploring FPGA-specific Optimizations for Irregular OpenCL Applications

Tango: A Deep Neural Network Benchmark Suite for Various Accelerators

Tango: A Deep Neural Network Benchmark Suite for Various Accelerators

MapD Core database

Exact Selectivity Computation for Modern In-Memory Database Query Optimization

BitCracker: the first open source password cracking tool for memory units encrypted with BitLocker

BitCracker: BitLocker meets GPUs

caffe-android-opencl-fp16: Optimised Caffe with OpenCL supporting for less powerful devices such as mobile phones

HG-Caffe: Mobile and Embedded Neural Network GPU (OpenCL) Inference Engine with FP16 Supporting

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

AutoParallel-Fortran: A domain specific, automatically parallelising source-to-source compiler for Fortran-95 that takes scientific Fortran as input and produces parallel Fortran/OpenCL

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

gpussjoin: Set Similarity joins in the GPGPU paradigm

Speeding-up the Verification Phase of Set Similarity Joins in the GPGPU paradigm

wav2letter: Facebook AI Research Automatic Speech Recognition Toolkit

wav2letter++: The Fastest Open-source Speech Recognition System

GenASiS_Basics: Object-oriented Utilitarian Functionality for Large-scale Physics Simulations

Targeting GPUs with OpenMP Directives on Summit: A Simple and Effective Fortran Experience

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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

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

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