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Oracle Solaris Studio 12.2: C User's Guide
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Document Information


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


Chapter 3

Parallelizing C Code

The Oracle Solaris Studio C compiler can optimize code to run on shared-memory multiprocessor/multicore/multithreaded systems. The compiled code can execute in parallel using the multiple processors on the system. Both automatic and explicit parallelization methods are available. This chapter explains how you can take advantage of the compiler’s parallelizing features.