zara
/
cuda-samples
mirror of https://github.com/NVIDIA/cuda-samples.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity
Samples for CUDA Developers which demonstrates features in CUDA Toolkit
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
376 Commits
1 Branch
25 Tags
177 MiB
 
 
 
 
Branch: master
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from 'master'
${ noResults }
cuda-samples/Samples/5_Domain_Specific/MonteCarloMultiGPU
Rob Armstrong 14b1bfdcc4
Replace README references to "CUDA Toolkit 12.5" with general "CUDA Toolkit" 		2 months ago
..
.vscode add and update samples for CUDA 11.6 4 years ago
doc add and update samples for CUDA 11.6 4 years ago
CMakeLists.txt Update all sample CMakeLists.txt to include ENABLE_CUDA_DEBUG flag to enable cuda-gdb 3 months ago
MonteCarloMultiGPU.cpp Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks. 3 months ago
MonteCarlo_common.h Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks. 3 months ago
MonteCarlo_gold.cpp Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks. 3 months ago
MonteCarlo_kernel.cu Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks. 3 months ago
MonteCarlo_reduction.cuh Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks. 3 months ago
README.md Replace README references to "CUDA Toolkit 12.5" with general "CUDA Toolkit" 2 months ago
multithreading.cpp Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks. 3 months ago
multithreading.h Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks. 3 months ago
realtype.h Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks. 3 months ago

README.md

MonteCarloMultiGPU - Monte Carlo Option Pricing with Multi-GPU support

Description

This sample evaluates fair call price for a given set of European options using the Monte Carlo approach, taking advantage of all CUDA-capable GPUs installed in the system. This sample use double precision hardware if a GTX 200 class GPU is present. The sample also takes advantage of CUDA 4.0 capability to supporting using a single CPU thread to control multiple GPUs

Key Concepts

Random Number Generator, Computational Finance, CURAND Library

Supported SM Architectures

SM 5.0 SM 5.2 SM 5.3 SM 6.0 SM 6.1 SM 7.0 SM 7.2 SM 7.5 SM 8.0 SM 8.6 SM 8.7 SM 8.9 SM 9.0

Supported OSes

Linux, Windows

Supported CPU Architecture

x86_64, armv7l

CUDA APIs involved

CUDA Runtime API

cudaStreamDestroy, cudaMalloc, cudaFree, cudaMallocHost, cudaSetDevice, cudaEventSynchronize, cudaGetDeviceProperties, cudaDeviceSynchronize, cudaEventRecord, cudaFreeHost, cudaMemset, cudaStreamSynchronize, cudaEventDestroy, cudaMemcpyAsync, cudaStreamCreate, cudaGetDeviceCount, cudaEventCreate

Dependencies needed to build/run

CURAND

Prerequisites

Download and install the CUDA Toolkit for your corresponding platform. Make sure the dependencies mentioned in Dependencies section above are installed.

References (for more details)

whitepaper