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Boda-RTC: Productive Generation of Portable, Efficient Code for Convolutional Neural Networks on Mobile Computing Platforms

Matthew Moskewicz, Forrest Iandola, Kurt Keutzer

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Tags: ARM, CNN, Computer science, Deep learning, Linear Algebra, Machine learning, Mathematical Software, Neural networks, OpenCL

June 7, 2016 by hgpu

Bit-Vectorized GPU Implementation of a Stochastic Cellular Automaton Model for Surface Growth

Jeffrey Kelling, Geza Odor, Sibylle Gemming

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Tags: Computational Physics, Computer science, CUDA, Materials Science, nVidia, nVidia GeForce GTX Titan X, nVidia GeForce Titan Black, Statistical Mechanics, Tesla K80

June 7, 2016 by hgpu

Co-tuning of Software Specializers and Hardware Accelerators within a CNN Application

Sean Roberts

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Tags: ARM, CNN, Computer science, Deep learning, FPGA, Neural networks, SoC

June 7, 2016 by hgpu

Development of Krylov and AMG linear solvers for large-scale sparse matrices on GPUs

Bo Yang, Hui Liu, Zhangxin Chen

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Tags: Computer science, CUDA, Linear Algebra, Mathematical Software, nVidia, Sparse linear iterative solvers, Sparse matrix, Tesla C2050, Tesla C2070

June 7, 2016 by hgpu

Challenges for a GPU-Accelerated Dynamic Programming Approach for Join-Order Optimization

Andreas Meister, Gunter Saake

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Tags: Algorithms, Computer science, Databases

June 2, 2016 by hgpu

Solver for Systems of Linear Equations with Infinite Precision on a GPU Cluster

Jiri Khun

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Tags: AMD Radeon HD 8750 M, ATI, Computer science, Extended precision, GPU cluster, Linear Algebra, Modular arithmetic, MPI, OpenCL

June 2, 2016 by hgpu

Disc: Approximative Nearest Neighbor Search using Ellipsoids for Photon Mapping on GPUs

Marcus Bergholm, Viktor Kronvall

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Tags: Algorithms, Computer science, CUDA, Image generation, Nearest neighbour, nVidia, nVidia GeForce GTX 970, Sorting, Thesis

June 2, 2016 by hgpu

Processing Posting Lists Using OpenCL

Radha Kotipalli

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Tags: Computer science, Intel HD Graphics 4000, nVidia Quadro K 2000 M, OpenCL, Thesis

June 2, 2016 by hgpu

Weighted Residuals for Very Deep Networks

Falong Shen, Gang Zeng

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X

June 2, 2016 by hgpu

clSPARSE: A Vendor-Optimized Open-Source Sparse BLAS Library

Joseph L. Greathouse, Kent Knox, Jakub Pola, Kiran Varaganti, Mayank Daga

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Tags: Algorithms, AMD Radeon R9 Fury X, ATI, Computer science, Linear Algebra, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Sparse matrix

May 30, 2016 by hgpu

TensorFlow: A system for large-scale machine learning

Martin Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zhang

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeFofce GTX Titan X, Package, Tesla K40

May 30, 2016 by hgpu

Bridging the Performance-Programmability Gap for FPGAs via OpenCL: A Case Study with OpenDwarfs

Konstantinos Krommydas, Ahmed E. Helal, Anshuman Verma, Wu-Chun Feng

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Tags: Benchmarking, Computer science, FPGA, Intel Xeon Phi, OpenCL, performance portability, Tesla C2070, Tesla K20

May 30, 2016 by hgpu

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

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