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Linux Parallel Processing HOWTO

Hank Dietz,

v980105, 5 January 1998

Parallel Processing refers to the concept of speeding-up the execution of a program by dividing the program into multiple fragments that can execute simultaneously, each on its own processor. A program being executed across N processors might execute N times faster than it would using a single processor. This document discusses the four basic approaches to parallel processing that are available to Linux users: SMP Linux systems, clusters of networked Linux systems, parallel execution using multimedia instructions (i.e., MMX), and attached (parallel) processors hosted by a Linux system.

1. Introduction

1.1 Is Parallel Processing What I Want?
1.2 Terminology
1.3 Example Algorithm
1.4 Organization Of This Document

2. SMP Linux

2.1 SMP Hardware
2.2 Introduction To Shared Memory Programming
2.3 bb_threads
2.4 LinuxThreads
2.5 System V Shared Memory
2.6 Memory Map Call

3. Clusters Of Linux Systems

3.1 Why A Cluster?
3.2 Network Hardware
3.3 Network Software Interface
3.4 PVM (Parallel Virtual Machine)
3.5 MPI (Message Passing Interface)
3.6 AFAPI (Aggregate Function API)
3.7 Other Cluster Support Libraries
3.8 General Cluster References

4. SIMD Within A Register (e.g., using MMX)

4.1 SWAR: What Is It Good For?
4.2 Introduction To SWAR Programming
4.3 MMX SWAR Under Linux

5. Linux-Hosted Attached Processors

5.1 A Linux PC Is A Good Host
5.2 Did You DSP That?
5.3 FPGAs And Reconfigurable Logic Computing

6. Of General Interest

6.1 Programming Languages And Compilers
6.2 Performance Issues
6.3 Conclusion - It's Out There

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