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Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application

Blesson Varghese, Javier Prades, Carlos Reano, Federico Silla

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Tags: Computer science, CUDA, Finance, nVidia, Tesla K20, Virtualization

August 12, 2015 by hgpu

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

Gordon Inggs, David B. Thomas, Wayne Luk

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Tags: AMD FirePro W5000, ATI, Computational finance, Computer science, Finance, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia Grid K2, nVidia Quadro K4000, OpenCL, Option pricing, Performance

May 20, 2015 by hgpu

GPU Accelerated framework for financial nested simulations

Joris Cramwinckel

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Tags: CUDA, Finance, nVidia, Risk Management, Tesla C2050, Tesla K20, Thesis

April 27, 2015 by hgpu

A Financial Benchmark for GPGPU Compilation

Christian Andreetta, Vivien Begot, Jost Berthold, Martin Elsman, Troels Henriksen, Maj-Britt Nordfang, Cosmin E. Oancea

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Tags: Benchmarking, Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 780 Ti

March 23, 2015 by hgpu

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

Blesson Varghese

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Tags: Computational Engineering, Computer science, CUDA, Finance, Intel Xeon Phi, nVidia, Performance, Tesla C2075

January 28, 2015 by hgpu

Methods and Metrics for Fair Server Assessment under Real-Time Financial Workloads

Giorgis Georgakoudis, Charles J. Gillan, Ahmed Sayed, Ivor Spence, Richard Faloon, Dimitrios S. Nikolopoulos

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Tags: ARM, Computer science, Finance, Intel Xeon Phi, Option pricing

January 5, 2015 by hgpu

High-accuracy Optimization by Parallel Iterative Discrete Approximation and Multi-GPU Computing

Di Zhao

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Tags: Biology, Computational biology, Computational finance, CUDA, Finance, nVidia, nVidia GeForce GTX 660, Thesis

November 13, 2014 by hgpu

Performance Engineering of the Kernel Polynomial Method on Large-Scale CPU-GPU Systems

Moritz Kreutzer, Georg Hager, Gerhard Wellein, Andreas Pieper, Andreas Alvermann, Holger Fehske

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Tags: Computational Engineering, CUDA, Finance, Mesoscale and Nanoscale Physics, nVidia, Tesla K20

October 22, 2014 by hgpu

GPU Implementation of a Deep Learning Network for Financial Prediction

Robin Kumar, Amandeep Kaur Cheema

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Tags: Artificial intelligence, Finance, Java, Machine learning, Neural networks, OpenCL

September 17, 2014 by hgpu

Accelerated Variance Reduction Methods on GPU

Chuan-Hsiang Han, Yu-Tuan Lin

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Tags: Algorithms, Computational finance, CUDA, Finance, Monte Carlo simulation, nVidia, nVidia GeForce GTX 690, Option pricing, Probability

September 15, 2014 by hgpu

High Performance Financial Simulation Using Randomized Quasi-Monte Carlo Methods

Linlin Xu, Giray Okten

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Tags: Algorithms, Computational finance, CUDA, Finance, nVidia, nVidia GeForce GTX 670

August 27, 2014 by hgpu

A Domain Specific Approach to Heterogeneous Computing: From Availability to Accessibility

Gordon Inggs, David Thomas, Wayne Luk

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Tags: Computational finance, Finance, FPGA, Heterogeneous systems, OpenCL, Option pricing, Package, Python

August 23, 2014 by hgpu

Neural Query Language: A Knowledge Base Query Language for Tensorflow

Neural Query Language: A Knowledge Base Query Language for Tensorflow

NMODL: Code Generation Framework For NEURON MODeling Language

An optimizing multi-platform source-to-source compiler framework for the NEURON MODeling Language

TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox

Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox

cuda-benches: collection of small CUDA benchmarking programs

Performance Engineering for a Tall & Skinny Matrix Multiplication Kernel on GPUs

Simulee: Charactering and Detecting CUDA Program Bugs

Charactering and Detecting CUDA Program Bugs

TensorNetwork: A TensorFlow library for easy and efficient manipulation of tensor networks

TensorNetwork: A Library for Physics and Machine Learning

jive

Principles, Techniques, and Tools for Explicit and Automatic Parallelization

caffe-mc-opencl: Caffe Deep Learning Software with Model Compression by Sparse Coding (Backend: OpenCL)

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Full-stack Optimization for Accelerating CNNs with FPGA Validation

Full-stack Optimization for Accelerating CNNs with FPGA Validation

AdaNet: Fast and flexible AutoML with learning guarantees

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

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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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