Is it beneficial to perform dimensionality reduction before fitting an SVM? Why or why not?

Is it beneficial to perform dimensionality reduction before fitting an SVM? Why or why not?

-When the number of features is large comparing to the number of observations (e.g. document-term matrix)
-SVM will perform better in this reduced space