Oli Tissot
MathWorks
Followers: 0 Following: 0
Feeds
已回答
Pcg and Parallel Computing Toolbox
You can simply do: dA = distributed(A); db = distributed(b); [dx, flag, iter] = pcg(dA, db, [], 100); % dx is a distributed a...
Pcg and Parallel Computing Toolbox
You can simply do: dA = distributed(A); db = distributed(b); [dx, flag, iter] = pcg(dA, db, [], 100); % dx is a distributed a...
4 years 前 | 0
已回答
Could `distributed array` accelerate the speed of solving Linear Equations with Iterative Methods?
This is somehow expected: distributed arrays are not meant to increase the speed of execution but to be used for arrays that are...
Could `distributed array` accelerate the speed of solving Linear Equations with Iterative Methods?
This is somehow expected: distributed arrays are not meant to increase the speed of execution but to be used for arrays that are...
4 years 前 | 1
| 已接受
已回答
Building Distributed/Codistributed Array with .mat files
The following should do what you want: ds = datastore('A_rowchunk_*.mat', 'Type', 'file', 'ReadFcn', @importdata, 'UniformRead'...
Building Distributed/Codistributed Array with .mat files
The following should do what you want: ds = datastore('A_rowchunk_*.mat', 'Type', 'file', 'ReadFcn', @importdata, 'UniformRead'...
4 years 前 | 1
已回答
What is the cause of the error of "CPARDISO encountered an error in phase 22: Error code = -2."?
Your guess is correct, you are getting this error because there is not enough local memory available. Some workarounds would be:...
What is the cause of the error of "CPARDISO encountered an error in phase 22: Error code = -2."?
Your guess is correct, you are getting this error because there is not enough local memory available. Some workarounds would be:...
4 years 前 | 1
| 已接受