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Parallel Algorithm for BSDEs Based High Dimensional American Option Pricing on the GPU

Ying Peng, Hui Liu, Shuzhen Yang, Bin Gong

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Tags: Algorithms, CUDA, Differential equations, Finance, nVidia, Tesla C2050

January 10, 2014 by hgpu

Multilayered Abstractions for Partial Differential Equations

Graham Robert Markall

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Code generation, CUDA, Differential equations, FEM, Finite element method, Mathematics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Partial differential equations, PDEs, Software Engineering, Thesis

December 11, 2013 by hgpu

Systematic Physics Constrained Parameter Estimation of Stochastic Differential Equations

Daniel Peavoy, Christian L. E. Franzke, Gareth O. Roberts

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Tags: Algorithms, Bayesian, CUDA, Differential equations, nVidia, Physics

December 9, 2013 by hgpu

GPU-Accelerated Crack Path Computation Based on a Phase Field Approach for Brittle Fracture

Alexander Schluter, Adrian Willenbucher, Charlotte Kuhn

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Tags: Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla C2075

December 8, 2013 by hgpu

Uses of GPU Powered Interval Optimization for Parameter Identification in the Context of SO Fuel Cells

Stefan Kiel, Ekaterina Auer, Andreas Rauh

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 580, ODEs, Ordinary differential equations

October 15, 2013 by hgpu

CUDA-Accelerated ODETLAP: A Parallel Lossy Compression Implementation

Daniel N. Benedetti, W. Randolph Franklin, Wenli Li

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Tags: Algorithms, Compression, CUDA, Differential equations, Image processing, nVidia, Partial differential equations, PDEs, Thrust

October 10, 2013 by hgpu

Multi-GPU Acceleration of Black-Scholes Equation based Option Pricing

Di Zhao, Jinhang Yu

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Tags: Algorithms, CUDA, Differential equations, Finance, nVidia, nVidia GeForce GTX 660, Partial differential equations, PDEs

September 23, 2013 by hgpu

Exponential Integrators on Graphics Processing Units

Lukas Einkemmer, Alexander Ostermann

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Tags: Computer science, CUDA, Differential equations, Numerical Analysis, nVidia, Tesla C1060, Tesla C2075

September 20, 2013 by hgpu

Simulation and modeling of physical broadcasts

Ahmed Ahmed

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Tags: Cellular automata, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 680, Thesis

September 13, 2013 by hgpu

Synthesis of Custom Networks of Heterogeneous Processing Elements for Complex Physical System Emulation

Chen Huang, Bailey Miller, Frank Vahid, Tony Givargis

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Tags: Computer science, CUDA, Differential equations, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 460, ODEs, Ordinary differential equations

August 23, 2013 by hgpu

From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation

Marek Blazewicz, Ian Hinder, David M. Koppelman, Steven R. Brandt, Milosz Ciznicki, Michal Kierzynka, Frank Loffler, Erik Schnetter, Jian Tao

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Tags: Code generation, Computational Physics, CUDA, Differential equations, Finite difference, MPI, nVidia, OpenMP, Partial differential equations, PDEs, Physics, Tesla M2050

July 25, 2013 by hgpu

CUDA-C implementation of the ADER-DG method for linear hyperbolic PDEs

C. E. Castro, J. Behrens, C. Pelties

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Tags: CUDA, Differential equations, Earth and Space Sciences, Geoscience, Hyperbolic PDEs, Matrix multiplication, nVidia, Partial differential equations, PDEs, Tesla C2070

July 15, 2013 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

Parallel Algorithm for BSDEs Based High Dimensional American Option Pricing on the GPU

Multilayered Abstractions for Partial Differential Equations

Systematic Physics Constrained Parameter Estimation of Stochastic Differential Equations

GPU-Accelerated Crack Path Computation Based on a Phase Field Approach for Brittle Fracture

Uses of GPU Powered Interval Optimization for Parameter Identification in the Context of SO Fuel Cells

CUDA-Accelerated ODETLAP: A Parallel Lossy Compression Implementation

Multi-GPU Acceleration of Black-Scholes Equation based Option Pricing

Exponential Integrators on Graphics Processing Units

Simulation and modeling of physical broadcasts

Synthesis of Custom Networks of Heterogeneous Processing Elements for Complex Physical System Emulation

From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation

CUDA-C implementation of the ADER-DG method for linear hyperbolic PDEs

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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