Download A Systolic Array Parallelizing Compiler by Ping-Sheng Tseng PDF

By Ping-Sheng Tseng

ISBN-10: 1461288355

ISBN-13: 9781461288350

Widespread use of parallel processing turns into a truth provided that the method of porting purposes to parallel desktops may be principally computerized. often it truly is common for a person to figure out how an software may be mapped onto a parallel laptop; in spite of the fact that, the particular improvement of parallel code, if performed by way of hand, is usually tough and time eating. Parallelizing compilers, that may gen­ erate parallel code immediately, are as a result a key expertise for parallel processing. during this ebook, Ping-Sheng Tseng describes a parallelizing compiler for systolic arrays, known as AL. even if parallelizing compilers are very common for shared-memory parallel machines, the AL compiler is without doubt one of the first operating parallelizing compilers for dispensed­ reminiscence machines, of which systolic arrays are a distinct case. The AL compiler takes benefit of the advantageous grain and excessive bandwidth interprocessor verbal exchange features in a systolic structure to generate effective parallel code. xii Foreword whereas able to dealing with a major classification of functions, AL isn't meant to be a general-purpose parallelizing compiler.

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41 Loop Distribution From the simple loop distribution model, we know that the intercell communication pattern of a distributed loop is solely determined by the intersection pattern of its data compatibility classes. Therefore, we can use the intersection pattern of data compatibility classes to design loop distribution schemes to match the communication architecture of the linear systolic array. 2 The basic loop distribution scheme Consider the data compatibility classes of linearly related DARRAYs U X"[d,,.

On the other hand, there is some run-time overhead associated with locally scoped data compatibility classes. For example, consider the following program: DARRAY int A[100] , B[100] , C[100], D[100] DO* (i = 0, n) { A[2*i] = B[4*i+3] + C[i+1]; } DO* (i = 1, m) { A[i] = B[3*i] + B[3*i+1] + D[i] } Since the compiler cannot construct joint data compatibility classes from the two DO* loops, each DO* loop defines the scope of its own set of data compatibility classes. The program starts with the data compatibility classes formed for the first DO* loop, then moves slices of DARRAYs A and B to form data compatibility classes for the sec- Data relations 35 ond DO* loop after the first DO* loop is executed.

Apply is a language for defining window operators on an image. The Apply compiler takes the definition of a window operator and generates a W2 program which reads in an image, applies the operator to all the pixels, and writes out the transformed image. Although Apply has a very limited application domain, it is an example of array-oblivious systolic array programming. There are other research projects on compiling programs for distributed memory parallel computers. Callahan and Kennedy [4] extended FORTRAN77 with DISTRlBUTE and DECOMPOSE statements for data distribution and studied parallelizing compiler techniques for distributed memory parallel computers in general and the Intel hypercube iPSC/2 in particular.

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