What was done ?
1) Improved timings by identifying sources of runtime bottlenecks (matrix multiplication in Range Finder).
Current timings : (100 components, 100 partitions, 100 node cluster)
10000 x 2000 - 2 min 51 sec
50000 x 10000 - 3 min 21 sec
100000 x 10000 - 6 min
2) Experimented with sparse matrix multiplication in blocked format using eigen library
Observations :
i) Using CSC forma for storage reduce cost of distributing blocks.
ii) After local multiplication, blocks are no longer sparse. This becomes a bottleneck since we do not get any benefit from sparse addition (axpy), but bringing sparse blocks in and out of C++ is time consuming.
Thus, this approach is viable in its current state.
What needs to be done ?
1) Continue working with sparse matrix multiplication to experiment with other approaches.
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