Basic concepts of parallelization

compiler design

1. BASIC CONCEPTS OF PARALLELIZATION (CD) by, K.B.Snega,M.sc(CS )., NADAR SARASWATHI COLLEGE OF ARTS AND SCIENCE,THENI

2. Parallel programming model A programming model is a collection of program abstraction providing a programmer a simplified and transparent view of computer H/W and S/W. A parallel programming is an abstraction of parallel computer architecture with which it is convenient to express algorithms and their composition in programs.

3. Five model are designed that exploits parallelism : Shared-variable model. Message-passing model. Data parallel model. Object oriented model. Functional and logic model.

4. SHARED VARIABLE MODEL Variables may be shared or restricted. These model can automatically generate the appropriate communication statements based on shared variable for SPMD(Simple Program Multiple data).

5. MESSAGE PASSING MODEL Synchronous Message Passing –  It is must synchronize the sender process and the receiver process in time and space. Asynchronous Message Passing –  It does not require message sending and receiving be synchronized in time and space.  Non blocking can be achieved. Distributing the computations-  Subprogram level is handled rather than at the instructional or fine grain process level in a tightly coupled multiprocessor.

6. DATA PARALLEL MODEL It is easier to write and to debug because parallelism is explicitly handled by hardware synchronization and flow control. It requires the use of pre-distributed data sets. Synchronization is done at compile time rather than run time. The following are some issued handled Data Parallelism Array Language Extensions Compiler support

7. OBJECT ORIENTED MODEL Object are created and manipulated dynamically. Processing is performed using object. Concurrent programming model are built up from low level object such as processes, queue and semaphore. C- oop achieve parallelism using three methods, 1.pipeline concurrency 2.Divide and conquer concurrency 3.Co-operating problem solving

8. FUNCTIONAL AND LOGICAL MODEL Two language-oriented programming for parallel processing are purposed. Functional programming model such as LISP, SISAL, Strand 88. Logic programming model as prolog. Based on predicate logic, logic programming is suitable for solving large database queries.

9. PARALLEL CONTROL LANGUAGE Special language construct and data array expression for exploiting parallelism in program. First is FORTRAN 90 array notation. Parallel flow control is achieve using do across and do all type of keyword which is use in the FORTRAN 90. Same we also use FORK and JOIN method.

10. OPTIMIZING COMPILER The role of compiler to remove the burden of program optimization and code generation. A parallelizing compiler consist of the three major phases. Flow analysis. Optimization. Code generation.

11. “Compilation phases in parallel code generation”

12. ISSUES IN PARALLELIZATION Amount of parallelizable CPU bound work. Task Granularity. Load Balancing. Memory allocation and Garbage collection. Locality issues.