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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

Monte-Carlo Black-Scholes Implementation using OpenCL Standard

Chirag Patel, M. Srikanth, Kalyani Chetan Kumar, S. Sivanantham

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Tags: Finance, FPGA, OpenCL

April 9, 2016 by hgpu

Classiffication-based Financial Markets Prediction using Deep Neural Networks

Matthew Dixon, Diego Klabjan, Jin Hoon Bang

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

April 3, 2016 by hgpu

GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model

Tetsuya Takaishi

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Tags: Bayesian, Computational finance, CUDA, Finance, Fortran, nVidia, nVidia GeForce GTX 760, OpenACC

March 29, 2016 by hgpu

Accelerating the Critical Line Algorithm for Portfolio Optimization Using GPUs

Raja H. Singh, Lee Barford, Frederick Harris Jr.

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Tags: Algorithms, Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 780

February 1, 2016 by hgpu

Free-form interest rate term structure decomposition: a 2nd order optimization problem

Brian Barnard

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Tags: Finance, Optimization, term structure decomposition

December 14, 2015 by little_jimmy

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

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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

Monte-Carlo Black-Scholes Implementation using OpenCL Standard

Classiffication-based Financial Markets Prediction using Deep Neural Networks

GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model

Accelerating the Critical Line Algorithm for Portfolio Optimization Using GPUs

Free-form interest rate term structure decomposition: a 2nd order optimization problem

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

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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