Download e-book for kindle: A Systolic Array Parallelizing Compiler by Ping-Sheng Tseng

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By Ping-Sheng Tseng

ISBN-10: 1461288355

ISBN-13: 9781461288350

ISBN-10: 146131559X

ISBN-13: 9781461315599

Widespread use of parallel processing turns into a fact provided that the method of porting functions to parallel desktops should be principally computerized. often it really is elementary for a person to figure out how an software could be mapped onto a parallel desktop; notwithstanding, the particular improvement of parallel code, if performed by means of hand, is usually tough and time eating. Parallelizing compilers, that can gen­ erate parallel code instantly, are as a result a key expertise for parallel processing. during this ebook, Ping-Sheng Tseng describes a parallelizing compiler for systolic arrays, referred to as AL. even supposing parallelizing compilers are very common for shared-memory parallel machines, the AL compiler is among the first operating parallelizing compilers for dispensed­ reminiscence machines, of which systolic arrays are a unique case. The AL compiler takes good thing about the high-quality grain and excessive bandwidth interprocessor conversation features in a systolic structure to generate effective parallel code. xii Foreword whereas in a position to dealing with a big category of purposes, AL isn't meant to be a general-purpose parallelizing compiler.

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The compiler generates code for each cell to identify the slices which belong to its local space and to execute the corresponding iterations. Iterations of this DO loop are executed in parallel, because they are distributed and no communication is needed among them. 3 shows an AL compiler generated W2 matrix factorization program for the lO-celi Warp machine. For this particular example, the compiler distributes data slices by assigning slice A[ i] to cell (i modulo 10). Systolic array programming 17 float a [50] [500], row[500]; int k, i, fe, fi, ee, ei, lj; for k := 0 to n do { if (eellid = (k 1.

Formally, the blocking scheme assigns data compatibility class Ci to cell Loop Distribution Li/wJ 43 of the systolic array, where w is a parameter to be deter- mined by the compiler. The blocking scheme not only localizes the communication for updating distributed variables but also localizes the communication for updating normal variables because two consecutive loop iterations are either executed in the same cell, which requires no communication, or in two neighboring cells, which only requires local communication.

The AL compiler generates code for a linear systolic array which supports fine-grain (a word per session), local (between two neighbors only), and stream-style communication, whereas the others generate code for hypercube systems which support large-grain (a message per session), global (between any two nodes in the system), and datagramstyle communication. Data relations 21 Chapter 3 Data relations In the previous chapter, we introduced the basic concepts of loop distribution. We considered the cases where each loop iteration only references one DARRAY slice.

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A Systolic Array Parallelizing Compiler by Ping-Sheng Tseng

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