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Oracle Solaris Studio 12.2: C User's Guide
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1.  Introduction to the C Compiler

2.  C-Compiler Implementation-Specific Information

3.  Parallelizing C Code

3.1 Overview

3.1.1 Example of Use

3.2 Parallelizing for OpenMP

3.2.1 Handling OpenMP Runtime Warnings

3.3 Environment Variables





3.3.5 Using restrict in Parallel Code

3.4 Data Dependence and Interference

3.4.1 Parallel Execution Model

3.4.2 Private Scalars and Private Arrays

3.4.3 Storeback

3.4.4 Reduction Variables

3.5 Speedups

3.5.1 Amdahl's Law Overheads Gustafson's Law

3.6 Load Balance and Loop Scheduling

3.6.1 Static or Chunk Scheduling

3.6.2 Self Scheduling

3.6.3 Guided Self Scheduling

3.7 Loop Transformations

3.7.1 Loop Distribution

3.7.2 Loop Fusion

3.7.3 Loop Interchange

3.8 Aliasing and Parallelization

3.8.1 Array and Pointer References

3.8.2 Restricted Pointers

3.8.3 Explicit Parallelization and Pragmas Serial Pragmas Parallel Pragma

Nesting of for Loops

Eligibility for Parallelizing

Number of Processors

Classifying Variables

Default Scoping Rules for private and shared Variables

private Variables

shared Variables

readonly Variables

storeback Variables


reduction Variables

Scheduling Control

3.9 Memory Barrier Intrinsics

4.  lint Source Code Checker

5.  Type-Based Alias Analysis

6.  Transitioning to ISO C

7.  Converting Applications for a 64-Bit Environment

8.  cscope: Interactively Examining a C Program

A.  Compiler Options Grouped by Functionality

B.  C Compiler Options Reference

C.  Implementation-Defined ISO/IEC C99 Behavior

D.  Supported Features of C99

E.  Implementation-Defined ISO/IEC C90 Behavior

F.  ISO C Data Representations

G.  Performance Tuning

H.  The Differences Between K&R Solaris Studio C and Solaris Studio ISO C


3.1 Overview

The C compiler generates parallel code for those loops that it determines are safe to parallelize. Typically, these loops have iterations that are independent of each other. For such loops, it does not matter in what order the iterations are executed or if they are executed in parallel. Many, though not all, vector loops fall into this category.

Because of the way aliasing works in C, it is difficult to determine the safety of parallelization. To help the compiler, Solaris Studio C offers pragmas and additional pointer qualifications to provide aliasing information known to the programmer that the compiler cannot determine. See Chapter 5, Type-Based Alias Analysis for more information.

3.1.1 Example of Use

The following example illustrates how to enable and control parallelized C:

% cc -fast -xO4 -xautopar example.c -o example

This generates an executable called example, which can be executed normally. If you wish to take advantage of multiprocessor execution, see B.2.75 -xautopar.