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Husmann, Harlan Edward 2014-12-15T19:25:47Z 2014-12-15T19:25:47Z 10000-01-01 1986 1986 The first part of this thesis deals with managing data in the multi-level memories of a tightly-coupled multiprocessor. One of the problems with this type of multiprocessor is the slow global memory. We examine how a compiler can use data dependence information to determine how data is used in a program, and then transform the program to exploit features in the multiprocessor's architecture to reduce the program's memory access time. The compiler/architecture techniques this thesis examines are allocating data to faster local memories, using a pipelined interconnection network, and overlapping global memory access with other operations. We present data from Parafrase-based experiments that measure the effectiveness of these techniques. The second part of this thesis examines two algorithms for partitioning a program into compound functions (tasks) for the multiprocessor. One algorithm examines the amount of parallelism in each loop of a program to find compound functions. The other algorithm estimates performance for every different way the loops in a program can execute (i.e., serial or parallel). After all estimates have been compared, the program is partitioned to minimize the overall execution time of the program. The effectiveness of these two algorithms is shown with empirical data gathered with Parafrase. Made available in DSpace on 2014-12-15T19:25:47Z (GMT). No. of bitstreams: 1 8701513.pdf: 6567070 bytes, checksum: fce043682e5d40e07da661974ed1e409 (MD5) Previous issue date: 1986 Embargo set by: Seth Robbins for item 69725 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 202 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1986. http://hdl.handle.net/2142/69559 (UMI)AAI8701513 Computer Science Compiler Memory Management and Compound Function Definition for Multiprocessors text Computer Science Computer Science University of Illinois at Urbana-Champaign Dissertation Ph.D.