efficient method for making a binary classifier multiclass?

I am attempting to use binary SVM classification on a 10 class set. It is important to do this as 1 vs 1 binary, because each pair of classes is best separated by a particuluar subset of attributes (as determined with SVM weights). However, training the 45 classifiers this would require would be very time consuming. Does anyone have any experience or advice?