Trying to simulate SOCP optimization problem using multiple class SVM for MNIST data. Could see that with solver set to ECOS, cvxpy compilation takes days to complete it.
CVXPY
v1.2.0
(CVXPY) Apr 20 03:59:48 PM: Your problem has 25680 variables, 45000 constraints, and 0 parameters.
(CVXPY) Apr 20 03:59:48 PM: It is compliant with the following grammars: DCP, DQCP
(CVXPY) Apr 20 03:59:48 PM: (If you need to solve this problem multiple times, but with different data, consider using parameters.)
(CVXPY) Apr 20 03:59:48 PM: CVXPY will first compile your problem; then, it will invoke a numerical solver to obtain a solution.
Compilation
(CVXPY) Apr 20 04:00:00 PM: Compiling problem (target solver=ECOS).
(CVXPY) Apr 20 04:00:00 PM: Reduction chain: Dcp2Cone -> CvxAttr2Constr -> ConeMatrixStuffing -> ECOS
(CVXPY) Apr 20 04:00:00 PM: Applying reduction Dcp2Cone
(CVXPY) Apr 20 04:00:14 PM: Applying reduction CvxAttr2Constr
(CVXPY) Apr 20 04:00:15 PM: Applying reduction ConeMatrixStuffing
This is a sample text, but Reduction of ConeMatrixStuffing is taking huge time in specific. Any thing we can do here to reduce the time? Will CVXPY support big Data or atleast MNIST data set?
