Relative to our current work on SEJITS, autotuning, and “frictionless high performance software”:
- Start an autotuning DB for use by SEJITS as well as manual use. Challenge is to determine a schema for this info that could be used both for human queries and machine queries (eg via XMLRPC). Each time an autotuning parameter set is determined, add it to the DB.
- Use Archana’s and Kristal’s KCCA algorithms as as test case for “frictionless”. They are sparse-matrix eigenvalue solver problems.
- SEJITS: take Andrew Ng et al’s paper on mapping a variety of SML algorithms to “summation form” for GPU execution, and apply SEJITS to those computations.
- SEJITS: look at LAWN 223 (Cholesky factorization on GPU) and encapsulate it in a specializer.