并行计算 -凯发k8网页登录
在 cpu 和/或 gpu 上并行执行 matlab® 程序和 simulink® 仿真
使用 matlab 的并行计算通过桌面、集群和云中的 cpu 和 gpu 提供帮助您利用更多硬件资源的语言及工具。
无需更改任何代码即可实现并行计算,因为已有数百个函数支持自动并行计算和 gpu。
编写可移植的并行代码,无论是否有 parallel computing toolbox 的用户都可以运行,还可根据可用资源自动扩展。
只需编写一次并行代码,即可在不同的集群环境中执行。
使用本地多核处理器和 gpu 求解计算密集型问题,或扩展到计算集群。
适用产品:并行计算
主题
并行计算基础
- (parallel computing toolbox)
take advantage of parallel computing resources without requiring any extra coding. - interactively run loops in parallel using parfor (parallel computing toolbox)
convert afor
-loop into a scalableparfor
-loop. - (parallel computing toolbox)
perform a parameter sweep in parallel and plot progress during parallel computations.
simulink 中的并行仿真:
- running multiple simulations (simulink)
run multiple simulations from theparsim
andbatchsim
commands, and the multiple simulations panel in simulink editor.
在 matlab 中使用 gpu
- run matlab functions on a gpu (parallel computing toolbox)
supply agpuarray
argument to automatically run functions on a gpu.
扩展到集群和云
- scale up from desktop to cluster (parallel computing toolbox)
develop your parallel matlab® code on your local machine and scale up to a cluster. - (parallel computing toolbox)
run parallel code in matlab online™.
并行计算应用
- (deep learning toolbox)
explore options for deep learning with matlab in parallel and using multiple gpus, locally or in the cloud. - minimizing an expensive optimization problem using parallel computing toolbox (optimization toolbox)
example showing how to use parallel computing in both global optimization toolbox and optimization toolbox™ solvers.