Difference between SVM and GD/SGD?
Yes,gradient descent (GD) and Stochastic Gradient Descent(SGD) are Optimization functions.Objective of a Optimization function is  to give the best combinations of parameters for our algorithm which minimize the error.Support Vector Machine is the Classification algorithm and GD/SGD are the optimization functions use to find best optimal hyperplane(separator).

Gradient Descent’s cost-function(total error of the training set) iterates over ALL training samples

Stochastic Gradient Descent’s cost-function only accounts for ONE training sample, chosen at random