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Programming on Multi-Core Processors Using Pthreads (POSIX Threads) |
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Pthreads are defined as a set of C-language programming types and procedure calls,
implemented with a pthread.h header/include file and a thread library.
Solaris threads are easily
understood by someone familiar with POSIX threads, and while Java threads and the
multi-threading in the Win32 and OS/2 APIs are a little different . The subroutines,
which comprise the Pthreads APIs, can be formally grouped into three classes such as
Thread Management, Mutex Variables and Condition Variables. Threaded applications offer
potential performance gains and practical advantages over non-threaded applications
in several other ways as we can observe from the different programs.
Example programs using different APIs. Compilation and execution
of Pthread programs, programs numerical and non-numerical computations
are discussed using
different thread APIs to understand Performance issues on mutli-core processors.
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Example 4.1
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Pthread program Suite : Computing Kernels for Dense Marix Computation algorithms
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(Source - References :
Books
Multi-threading
-[MCMTh-01], [MCMTh-02], [MCMTh-I03], [MCMTh-05], [MCMth-09], [MCMth-11],
[MCMTh-15], [MCMTh-21], [MCBW-44] )
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Description of Pthreads Computing Kernels /Benchmarks |
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Example 4.1:
Suite of programs on Dense Matrix Computation Kernels on Multi-Core Processor systems.
( Download WinRAR ZIP archive:
In-House-Pthreads-Benchmarks-codes (WinRAR ZIP archive)
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- Objective
Performance of suite of programs on Dense Matrix Computation Kernels & other
numerical computation kernels on Multi-Core Processor systems.
- Description
This benchmark comprises of suites performing Integer / Floating-Point
Numerical and Non-Numerical computations using Shared Memory Programming
(Pthreads).
These suite of programs measure the execution time of kernels of Dense Matrix
Computations involving Computation of Square Matrix Norm by
Rowwise/Columnwise Partitioning ,Matrix and Vector Multiplication using
checkerboard algorithm & Matrix and Matrix Multiplication using self
scheduling algorithm ; PI computation using Numerical Integration and
Monte Carlo Method ; Solving the Linear equation Ax = b using Jacobi
Method ; and Sorting the given single dimension array for finding the
minimum integer.
- Input
The suites run for problem sizes - Class A,B,C on 1/2/4/8 threads as per run-rules.
- Output
This Multi-Core Benchmark suite of programs gives the performance of system in terms of
Time, Memory Utilized, Cpu Speed etc.
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