By Janusz S. Kowalik
Specialists in high-speed computation agree that the speedily transforming into call for for extra strong pcs can basically be met through an intensive switch in machine structure, a metamorphosis from a unmarried serial processor to an aggregation of many processors operating in parallel. at the moment, our wisdom approximately multi-processor architectures, concurrent programming or parallel algorithms is particularly constrained. This booklet discusses all 3 matters when it comes to the HEP supercomputer that may deal with a number of guide streams and a number of info streams (MIMD). The HEP multiprocessor is an cutting edge common goal machine, effortless to take advantage of by means of anyone conversant in FORTRAN. Following a preface through the editor, the book's fifteen unique contributions are divided into 4 sections: The HEP structure and platforms software program; The HEP functionality; Programming and Languages; and functions of the HEP desktop. An appendix describes using screens in FORTRAN, offering an academic at the barrier, self-scheduling DO loop, and Askfor screens. J. S. Kowalik, who has contributed a bankruptcy with S. P. Kumar on "Parallel Algorithms for Recurrence and Tridiagonal Linear Equations," is a supervisor in Boeing desktop companies' man made Intelligence middle in Seattle. MIMD Computation is integrated within the clinical Computation sequence, edited via Dennis Cannon.
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Extra resources for Parallel MIMD Computation: HEP Supercomputer and its Applications
Hardware and of the Fortran run-time system. The computation is in the form of a hinary tree in which an approximation and error estimate are applied to a subinterval at each node of the tree. If more accuracy is required, the subinterval is divided in two, and the same algorithm is applied to each new interval. Since the number of available processes is limited, it is not possible to assign every subinterval to a separate process, but a program which gives away subtrees of the computation when processes are available to do them can be designed and executed by one or many processes with the same numerical results.
This is the case in a true multiprocessor with P or more processors and is closely approximated in the pipelined ~lIMD hardware of a single HE? execution module, provided P is no more than about five. Above P= 5 single instruction stream lookahead begins to limit parallelism in HEP. Many applications programs discussed fit the required program format very well. They are composed of an arbitrary number of "self-scheduling," identical processes which result from a FORK near the beginning of the program and JOIN together near its end.
The third type of program is the "no nvectorizable" program. Experience suggests that few programs are completely nonvectorizable, but there is a distinct class of programs where MIMD parallelization is simpler Dr more natural than vectorlzatlon. Dluty Deck Pr oqr ams An idea of the best that can be expected from the pipelined MIMD architecture can be obtained by analysis of an easily parallelizcd program with a simple structure. The heart of this benchmark is a numerical integration to compute the Gamma function.
Parallel MIMD Computation: HEP Supercomputer and its Applications by Janusz S. Kowalik