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Optimising Convolutional Neural Networks Inference on Low-Powered GPUs

Simon Rovder, Jose Cano, Michael O'Boyle

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Tags: Computer science, Deep learning, Heterogeneous systems, Neural networks, OpenCL

February 10, 2019 by hgpu

Heterogeneous Distributed Big Data Clustering on Sparse Grids

David Pfander, Gregor Daiss, Dirk Pfluger

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Tags: Clustering, Computer science, Data mining, Distributed computing, Heterogeneous systems, Machine learning, MPI, nVidia, OpenCL, Package, performance portability, Tesla P100

February 10, 2019 by hgpu

Efficient Implementation and Optimization of Geometric Multigrid Operations in the LIFT Framework

Martin Lucke

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX 1080, OpenCL, Partial differential equations, PDEs, performance portability, Thesis

January 27, 2019 by hgpu

Direct N-body code on low-power embedded ARM GPUs

David Goz, Sara Bertocco, Luca Tornatore, Giuliano Taffoni

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Tags: ARM, Astrophysics, FPGA, Heterogeneous systems, Instrumentation and Methods for Astrophysics, N-body simulation, OpenCL, OpenMPI, SoC

January 27, 2019 by hgpu

Exploring FPGA-specific Optimizations for Irregular OpenCL Applications

Mohamed W. Hassan, Ahmed E. Helal, Peter M. Athanas, Wu-Chun Feng, Yasser Y. Hanafy

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Tags: Benchmarking, Computer science, FPGA, HLS, Linear Algebra, OpenCL, Package

January 20, 2019 by hgpu

Tango: A Deep Neural Network Benchmark Suite for Various Accelerators

Aajna Karki, Chethan Palangotu Keshava, Spoorthi Mysore Shivakumar, Joshua Skow, Goutam Madhukeshwar Hegde, Hyeran Jeon

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Tags: Benchmarking, Computer science, CUDA, Deep learning, FPGA, Machine learning, Neural networks, nVidia, nVidia Jetson TX1, OpenCL, Package

January 20, 2019 by hgpu

Auto-tuned OpenCL kernel co-execution in OmpSs for heterogeneous systems

B. P'erez, E. Stafford, J. L. Bosque, R. Beivide, S. Mateo, X. Teruel, X. Martorell, E. Ayguad'e

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Tags: Computer science, Heterogeneous systems, nVidia, OmpSs, OpenCL, Tesla K20

January 13, 2019 by hgpu

BitCracker: BitLocker meets GPUs

Elena Agostini, Massimo Bernaschi

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Tags: AES, ATI, ATI Radeon HD 7990, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, nVidia GeForce GTX Titan X, OpenCL, Package, Security, Tesla K80, Tesla P100, Tesla V100

January 13, 2019 by hgpu

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

Zhuoran Ji

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Tags: Caffe, Computer science, Deep learning, Machine learning, Neural networks, OpenCL, Package

January 13, 2019 by hgpu

HeteroCL: A Multi-Paradigm Programming Infrastructure for Software-Defined Reconfigurable Computing

Yi-Hsiang Lai, Yuze Chi, Yuwei Hu, Jie Wang, Cody Hao Yu, Yuan Zhou, Jason Cong, Zhiru Zhang

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Tags: Algorithms, Compilers, Computer science, FPGA, Heterogeneous systems, HLS, OpenCL, Python

January 6, 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

A Survey on Optimized Implementation of Deep Learning Models on the NVIDIA Jetson Platform

Sparsh Mittal

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia Jetson TK1, nVidia Jetson TX1, nVidia Jetson TX2, OpenCL, survey

December 30, 2018 by hgpu

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Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

See all packages

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high performance computing on graphics processing units: hgpu.org

Optimising Convolutional Neural Networks Inference on Low-Powered GPUs

Heterogeneous Distributed Big Data Clustering on Sparse Grids

Efficient Implementation and Optimization of Geometric Multigrid Operations in the LIFT Framework

Direct N-body code on low-power embedded ARM GPUs

Exploring FPGA-specific Optimizations for Irregular OpenCL Applications

Tango: A Deep Neural Network Benchmark Suite for Various Accelerators

Auto-tuned OpenCL kernel co-execution in OmpSs for heterogeneous systems

BitCracker: BitLocker meets GPUs

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

HeteroCL: A Multi-Paradigm Programming Infrastructure for Software-Defined Reconfigurable Computing

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

A Survey on Optimized Implementation of Deep Learning Models on the NVIDIA Jetson Platform

Recent source codes

E2C-Sim: a simulator and workload generator for Edge-to-Cloud environments

Kernel Tuner

Clava: C/C++ Source-to-Source Tool based on Clang

gpuLik

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

BAT: A standardized benchmark suite for auto-tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

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