Researcher: Prof. Prithviraj Banerjee,
The PARADIGM compiler is targeted for both structured and unstructured parallel
numerical applications written in FORTRAN 77
and High Performance Fortran.
The sequential FORTRAN programs for regular applications
are automatically parallelized using a parallelizing
compiler (Parafrase-2), and the PARADIGM compiler
performs
several compiler transformations on the
program, and then generates efficient message
passing FORTRAN code.
Numerous compiler optimizations
such as loop bound reduction, mask extraction
and elimination, message vectorization,
message chaining, message aggregation
are automatically performed by the PARADIGM compiler.
In addition, the PARADIGM compiler is unique in
its ability
The PARADIGM compiler is being evaluated on the IBM SP-2 and networks
of workstations for a variety of regular and irregular applications
written in Fortran. Ongoing work is to work on distributed shared
memory machines such as the SGI Origin.
The work has been funded by the National Science Foundation.
The PARADIGM team currently includes:
Problem Description
Distributed memory message passing machines such as the
IBM SP-2, the Intel Paragon,
and the Thinking Machines CM-5 offer significant
advantages over shared-memory multiprocessors in terms of cost and
scalability.
Unfortunately, to extract all that computational power from these
machines, users have to write efficient software for them, which is an
extremely laborious process. One major reason for this difficulty is
the absence of a single global shared address space. As a result, the
programmer himself has to manually
distribute code and data on processors, and
manage communication among tasks explicitly. Clearly, there is a need
for efficient parallel programming support on these machines.
The PARADIGM
compiler project addresses that problem by developing
an automated means to convert sequential programs,
automatically parallelizing them by
compiler dependence analysis,
and compiling them for
efficient execution on distributed memory machines.
Project Overview:
What sets the PARADIGM project apart from other compiler efforts for
distributed-memory multicomputers is the broad range of research topics
that are being addressed.
Current research topics in the PARADIGM project have been focused in
the following areas:
Research Results
(1) to perform automated data distribution
for regular data structures;
(2) to support simultaneous exploitation of task and data parallelism;
(3) to exploit regularity within irregularity
in iterative applications.
(4) to handle arbitrary block-cyclic data distributions
and arbitrary data alignments.
Publications
Team Members:
Group Alumni:
Other Related Work:
Send any questions to
Professor Banerjee