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Investigating Input Representations and Representation Models of Source Code for Machine Learning

Alexander Brauckmann

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Tags: AMD Radeon HD 7970, ATI, Code generation, Computer science, LLVM, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 970, OpenCL, Thesis

July 12, 2020 by hgpu

Deep Learning for Compilers

Chris Cummins

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Tags: AMD Radeon HD 7970, ATI, Benchmarking, Compilers, Computer science, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 970, OpenCL, Package, Thesis

April 5, 2020 by hgpu

Improving GPU Performance through Instruction Redistribution and Diversification

Xiang Gong

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Tags: AMD Radeon HD 7970, ATI, Compilers, Computer science, OpenCL, Optimization, Thesis

March 10, 2019 by hgpu

RAPIDNN: In-Memory Deep Neural Network Acceleration Framework

Mohsen Imani, Mohammad Samragh, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, Tajana Rosing

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Tags: AMD Radeon HD 7970, ATI, CNN, Computer science, Deep learning, FPGA, Hardware Architecture, Neural networks, OpenCL

June 20, 2018 by hgpu

Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures

Beau Johnston, Josh Milthorpe

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Tags: AMD FirePro S9150, AMD Radeon HD 7970, AMD Radeon R9 290X, AMD Radeon R9 Fury X, AMD Radeon RX 480, ATI, Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, OpenCL, Tesla K20, Tesla K40

May 12, 2018 by hgpu

CANNA: Neural Network Acceleration using Configurable Approximation on GPGPU

Mohsen Imani, Max Masich, Daniel Peroni, Pushen Wang, Tajana Rosing

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Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Neural networks, OpenCL

April 22, 2018 by hgpu

Merge or Separate? Multi-job Scheduling for OpenCL Kernels on CPU/GPU Platforms

Yuan Wen, Michael F.P. O'Boyle

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Tags: AMD Radeon HD 7970, ATI, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 780, OpenCL

April 3, 2017 by hgpu

Fast reconstruction of 3D volumes from 2D CT projection data with GPUs

M. Leeser, S. Mukherjee, J. Brock

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Tags: AMD, AMD Radeon HD 7970, Computed tomography, CT, CUDA, Heterogeneous systems, Medicine, nVidia, OpenCL, Tesla C2075

September 1, 2014 by hgpu

cuSZ: CUDA-Based Error-Bounded Lossy Compressor for Scientific Data

A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression

Ginkgo: a high-performance linear algebra library for manycore systems

Ginkgo – A Math Library designed for Platform Portability

GPURepair

GPURepair: Automated Repair of GPU Kernels

Dazmir

Adaptive Data Migration in Load-Imbalanced HPC Applications

ACA-project

Runtime Performances Benchmark for Knowledge Graph Embedding Methods

TornadoVM

Transparent Compiler and Runtime Specializations for Accelerating Managed Languages on FPGAs

AMGCL

AMGCL – A C++ library for efficient solution of large sparse linear systems

Tinker-HP: High Performance Multi-GPUs Massively Parallel Evolution of Tinker

Tinker-HP: Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields using GPUs and Multi-GPUs systems

EngineCL: Usability and Performance in Heterogeneous Computing

Towards Co-execution on Commodity Heterogeneous Systems: Optimizations for Time-Constrained Scenarios

Neural Network Libraries

Out-of-core Training for Extremely Large-Scale Neural Networks With Adaptive Window-Based Scheduling

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2020

December

10-14

Virtually in Barcelona, Spain

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

2020

November

24-27

Naha, Okinawa, Japan

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2021

January

13-15

Shenzhen, China

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

2020

December

14-16

Bangkok, Thailand

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020

2020

December

14-16

Bangkok, Thailand

International Conference on Wireless Networks and Embedded Systems (ICWNES’20), 2020

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