high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Finance

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

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

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Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

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

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

Recent source codes

E2C-Sim: a simulator and workload generator for Edge-to-Cloud environments

Kernel Tuner

Clava: C/C++ Source-to-Source Tool based on Clang

gpuLik

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

BAT: A standardized benchmark suite for auto-tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

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