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A parallel implementation of a derivative pricing model incorporating SABR calibration and probability lookup tables

Qasim Nasar-Ullah

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Tags: Computational finance, Computer science, CUDA, Finance, nVidia, Tesla M2070

January 16, 2013 by hgpu

Exploration of Parallelization Frameworks for Computational Finance

Raj B Krishnamurthy, Ikubin Chin, Anjil Chinnapatlolla

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Tags: Computational finance, Finance, OpenCL

September 22, 2012 by hgpu

Using high performance computing and Monte Carlo simulation for pricing american options

Verche Cvetanoska, Toni Stojanovski

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Tags: Computational finance, Computer science, CUDA, Finance, Monte Carlo simulation, nVidia, nVidia GeForce GT 540 M

May 3, 2012 by hgpu

A Normalized Particle Swarm Optimization Algorithm to Price Complex Chooser Option and Accelerating its Performance with GPU

Bhanu Pratap Sharma

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Tags: Algorithms, Computational finance, CUDA, Finance, nVidia, nVidia GeForce GTX 450, nVidia GeForce GTX 550 Ti, Thesis

December 21, 2011 by hgpu

GPU Computing Gems: Jade Edition

Wen-mei W. Hwu

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Tags: Algorithms, Book, Cellular automata, Computational finance, Computer science, Computer vision, CUDA, Finance, Fluid dynamics, Games, GPU cluster, nVidia

October 14, 2011 by hgpu

Efficient reconfigurable design for pricing asian options

Anson H.T. Tse, David B. Thomas, K.H. Tsoi, Wayne Luk

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Tags: Computational finance, CUDA, Finance, FPGA, Tesla

October 8, 2011 by hgpu

Option pricing with COS method on graphics processing units

Bowen Zhang, Cornelis W. Oosterlee

Tags: Computational finance, Finance

July 6, 2011 by hgpu

Parallelization and characterization of GARCH option pricing on GPUs

Ren-Shuo Liu, Yun-Cheng Tsai, Chia-Lin Yang

Tags: Computational finance, CUDA, Finance, nVidia

June 17, 2011 by hgpu

Parallelized Local Volatility Estimation Using GP-GPU Hardware Acceleration

C.C. Douglas, Hyoseop Lee, Dongwoo Sheen

Tags: Algorithms, Computational finance, Finance

April 26, 2011 by hgpu

Financial Derivatives Modeling Using GPU’s

Myungho Lee, Chin Hong Chun, Sugwon Hong

Tags: Computational finance, Finance, Optimization

April 25, 2011 by hgpu

Challenges of mapping financial analytics to many-core architecture

M. Smelyanskiy

Tags: Computational finance, Finance

April 22, 2011 by hgpu

On Using GPU to Compute Options and Derivatives

Option Models

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Tags: Computational finance, CUDA, Finance, nVidia, nVidia GeForce 8800 GT

March 23, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

A parallel implementation of a derivative pricing model incorporating SABR calibration and probability lookup tables

Exploration of Parallelization Frameworks for Computational Finance

Using high performance computing and Monte Carlo simulation for pricing american options

A Normalized Particle Swarm Optimization Algorithm to Price Complex Chooser Option and Accelerating its Performance with GPU

GPU Computing Gems: Jade Edition

Efficient reconfigurable design for pricing asian options

Option pricing with COS method on graphics processing units

Parallelization and characterization of GARCH option pricing on GPUs

Parallelized Local Volatility Estimation Using GP-GPU Hardware Acceleration

Financial Derivatives Modeling Using GPU’s

Challenges of mapping financial analytics to many-core architecture

On Using GPU to Compute Options and Derivatives

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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