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Implementing Deep Neural Networks for Financial Market Prediction on the Intel Xeon Phi

Matthew Dixon, Diego Klabjan, Jin Hoon Bang

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Tags: Algorithms, CNN, Computer science, Deep learning, Finance, Intel Xeon Phi, Neural networks

May 26, 2016 by hgpu

PROJECTION Algorithm for Motif Finding on GPUs

Jhoirene B. Clemente, Francis George C. Cabarle, Henry N. Adorna

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Tags: Algorithms, Biology, Computational biology, CUDA, nVidia

May 26, 2016 by hgpu

Performance Evaluation of Parallel Count Sort using GPU Computing with CUDA

Neetu Faujdar, SatyaPrakash Ghrera

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Sorting

May 21, 2016 by hgpu

pyJac: analytical Jacobian generator for chemical kinetics

Kyle E. Niemeyer, Nicholas J. Curtis, Chih-Jen Sung

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Tags: Algorithms, Computational Physics, CUDA, Differential equations, Finite difference, nVidia, Package, Physics, Python, Tesla C2075

May 17, 2016 by hgpu

Attention-based NMT Models as Feature Functions in Phrase-based SMT

Marcin Junczys-Dowmunt, Tomasz Dwojak, Rico Sennrich

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Tags: Algorithms, Computer science, CUDA, Machine learning, NLP, nVidia, nVidia GeForce GTX 970

May 17, 2016 by hgpu

Parallelizing Word2Vec in Shared and Distributed Memory

Shihao Ji, Nadathur Satish, Sheng Li, Pradeep Dubey

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, NLP, nVidia, nVidia GeForce GTX Titan X, Tesla K40

May 9, 2016 by hgpu

Parallel Pairwise Correlation Computation On Intel Xeon Phi Clusters

Yongchao Liu, Tony Pan, Srinivas Aluru

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Tags: Algorithms, Bioinformatics, Computer science, Intel Xeon Phi, OpenMP

May 7, 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

On the design of sparse hybrid linear solvers for modern parallel architectures

Stojce Nakov

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, MPI, nVidia, Sparse linear iterative solvers, Sparse matrix, Tesla K40, Tesla M2070, Thesis

April 29, 2016 by hgpu

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

Nilothpal Talukder

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Tags: Algorithms, Computer science, CUDA, Data mining, Databases, MPI, nVidia, Tesla C2075, Thesis

April 29, 2016 by hgpu

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

Ilya Loshchilov, Frank Hutter

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Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Package, Python

April 26, 2016 by hgpu

LightScan: Faster Scan Primitive on CUDA Compatible Manycore Processors

Yongchao Liu, Srinivas Aluru

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Tags: Algorithms, Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, PTX, Tesla K40

April 19, 2016 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

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

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

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

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

PyOMP: OpenMP for Python in Numba

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Implementing Deep Neural Networks for Financial Market Prediction on the Intel Xeon Phi

PROJECTION Algorithm for Motif Finding on GPUs

Performance Evaluation of Parallel Count Sort using GPU Computing with CUDA

pyJac: analytical Jacobian generator for chemical kinetics

Attention-based NMT Models as Feature Functions in Phrase-based SMT

Parallelizing Word2Vec in Shared and Distributed Memory

Parallel Pairwise Correlation Computation On Intel Xeon Phi Clusters

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

On the design of sparse hybrid linear solvers for modern parallel architectures

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

LightScan: Faster Scan Primitive on CUDA Compatible Manycore Processors

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

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

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

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

PyOMP: OpenMP for Python in Numba

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