论文标题
解决GPU和CPU上的大量非Stift，低维的普通微分方程系统：MPGOS，ODEINT和DINCAINALEQUATIONS的性能比较。
Solving large number of non-stiff, low-dimensional ordinary differential equation systems on GPUs and CPUs: performance comparisons of MPGOS, ODEINT and DifferentialEquations.jl
论文作者
论文摘要
在本文中，研究了不同解决方案技术和程序包的性能特征，以解决大量独立的普通微分方程系统。使用的硬件是Intel Core i7-4820k CPU，每个内核具有30.4 Gflops Peak Double Excision性能和Nvidia Geforce Titan Black GPU，总共具有1707 GFLOPS峰值双重精确表现。测试的系统（Lorenz方程，Keller--Miksis方程和压力浮雕阀模型）是非Stiff的，并且具有较低的尺寸。因此，代码的性能不受内存带宽的限制，runge-kutta类型求解器是有效且合适的选择。经过测试的程序包是用C ++编写的MPGO，仅专门用于GPU。在C ++中实现的odeint，支持CPU和GPU上的执行；最后，用朱莉娅（Julia）撰写的《差异化》（Julialequations.jl）也支持CPU和GPU上的执行。使用GPU，程序包MPGO是优越的。对于CPU计算，Odeint程序软件包具有最佳性能。
In this paper, the performance characteristics of different solution techniques and program packages to solve a large number of independent ordinary differential equation systems is examined. The employed hardware are an Intel Core i7-4820K CPU with 30.4 GFLOPS peak double-precision performance per cores and an Nvidia GeForce Titan Black GPU that has a total of 1707 GFLOPS peak double-precision performance. The tested systems (Lorenz equation, Keller--Miksis equation and a pressure relief valve model) are non-stiff and have low dimension. Thus, the performance of the codes are not limited by memory bandwidth, and Runge--Kutta type solvers are efficient and suitable choices. The tested program packages are MPGOS written in C++ and specialised only for GPUs; ODEINT implemented in C++, which supports execution on both CPUs and GPUs; finally, DifferentialEquations.jl written in Julia that also supports execution on both CPUs and GPUs. Using GPUs, the program package MPGOS is superior. For CPU computations, the ODEINT program package has the best performance.
