high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Finance

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

Blesson Varghese, Javier Prades, Carlos Reano, Federico Silla

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

Source codes

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

August 23, 2014 by hgpu

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Efficient and Scalable k-Means on GPUs

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Integer sorting on multicore

A study of integer sorting on multicores

See all packages

* * *

2019

February

25-28

Shanghai, China

International Conference on Image, Video and Signal Processing (IVSP), 2019

2018

November

20-22

Khalifa University, Abu Dhabi, UAE

International Joint Conference on Signals, Systems and Computers (CSSC), 2018

2018

December

13-15

Wellington, New Zealand

International Joint Conference on Robotics, Automation and Mechatronics (JCRAM), 2018

2018

December

10-12

Wellington, New Zealand

International Joint Conference on Robotics and Artificial Intelligence (JCRAI), 2018

2018

December

13-15

Wellington, New Zealand

International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018

Add event

See all events

high performance computing on graphics processing units: hgpu.org

Applications

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

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

GPU Accelerated framework for financial nested simulations

A Financial Benchmark for GPGPU Compilation

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

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

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

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

GPU Implementation of a Deep Learning Network for Financial Prediction

Accelerated Variance Reduction Methods on GPU

High Performance Financial Simulation Using Randomized Quasi-Monte Carlo Methods

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

Recent source codes

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Integer sorting on multicore

Most viewed papers (last 30 days)

Featured events

International Conference on Image, Video and Signal Processing (IVSP), 2019

International Joint Conference on Signals, Systems and Computers (CSSC), 2018

International Joint Conference on Robotics, Automation and Mechatronics (JCRAM), 2018

International Joint Conference on Robotics and Artificial Intelligence (JCRAI), 2018

International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018