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License: GNU General Public License v3.0
Exact diagonalization library for general models
License: GNU General Public License v3.0
the basis with bits is not a good representation for dilute problems.
Motivated by HPhi project:
http://qlms.github.io/HPhi/index_en.html
may be proportional to mpi threads?
when changing schedule of one loop, another loop executed much earlier changes speed, unbelievable...
in each case, use either no symmetry or with translational symmetry
otherwise too dangerous...
partial and selective re-orthogonalization for home-made Lanczos with 3 vectors.
DGKS for home-made IRAM with ncv vectors.
boost version costing too much memory
motivated by Lauchli's chapter in Lacroix's book, similar to the divide and conquer idea.
The matrix storage can be distributed among different nodes by using PETSc, making the ~50 spin-1/2 problems feasible.
Also add locking and purging, to enhance stability.
need complete the implementation of mopr sum and product
when mkl distributed csr matrices support matrix-vector product, we can use it to parallelize the code on distributed machines.
For the following pattern, Lin Table failed to build. Need smarter labeling.
x x x
x o x
x x x
(horizontal axis for ia, vertical axis for ib. "o" represents no basis here)
possible?
Currently using bubble sort to count the "-" sign generated by lattice transformation. Need replace with quick sort in the future.
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