Why matlab performs much slower on a cluster with 144 cores than on a desktop with only 6 cores when solving a large system

Hello, everyone! Recently I'm trying to solve a quite large system Ax = b, with A an 353344*353344 sparse matrix and number of nonzeros is 22548736. The structure of the matrix is shown in Fig. 1.

Fig. 1 Structure of the sparse matrix A.

At present, only direct solver is adopted. I solve this system on both desktop and a cluster.

On desktop, the details are as follows:

Matalb version: R2017 a;

CPU: Intel(R) Xeon(R) CPU E5-2620 v3 @ 2.40GHz;

Cores: 6 cores;

Time elapsed: 20 seconds on average

On Cluster, the details are as follows:

Matlab version: R2017 b;

CPU: Intel(R) Xeon(R) CPU E7-8870 v3 @ 2.10GHz

Cores: 72 cores;

Time elapsed: 232 seconds on average

OMP_NUM_THREADS: 72

As far as I know, when solving such a problem, the Intel Math Kernel Library with openmp-parallelized LAPACK and BLAS is adopted. If so, the program on cluster should be faster than that on desktop even though the frequency is a little lower than that of the desktop.

Since this system need to be solved thounds of times, I urgently need to accelarete this process. Can anybody give any advices on this?