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Programming on Multi-Core Processors Using OpenMP APIs |
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The OpenMP API is used for writing portable multi-threaded applications written in Fortran, C and C++ languages.
The OpenMP programming model plays a key role by providing an easy method for threading applications without burdening
the programmer with the complications of creating, synchronizing load balancing, and destroying threads.
The OpenMP model provides a platform independent set of compiler pragmas, directives, function calls, and environment
variables that explicitly instruct the compiler how and where to use the parallelism in the application.
Example programs using
compiler pragmas, directives, function calls, and environment variables, Compilation and execution
of OpenMP programs and programs numerical and non-numerical computations
are discussed.
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Example 4.1
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OpenMP program : Computing Kernels for Matrix Computation
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(Source - References :
Books
Multi-threading
OpenMP
-[MCMTh-01], [MCMTh-02], [MCMTh-I03], [MCMTh-05], [MCMTh-09], [MCMTh-11],
[MCMTh-15], [MCMTh-21], [MCBW-44], [MCOMP-01], [MCOMP-02],
[MCOMP-04], [MCOMP-12], [MCOMP-19], [MCOMP-25])
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Description of OpenMP Computing Kernels /Benchmarks |
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Example 4.1 :
Performance of Matrix Computation Test Kernels on Multi-Cores :
( Download WinRAR ZIP archive:
OpenMP-In-House-Benchmarks-codes (WinRAR ZIP archive)
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- Objective
The main objective is to execute computing Kernels on Multi-cores and evaluate
the performance on Multi-Core systems for various problem sizes
and threads.
- Description
This benchmark comprises of suites performing Integer / Floating-Point
Numerical and Non-Numerical computations using Shared Memory Programming
(OpenMP).
These suites measures the execution time of kernels of Dense Matrix
Computations involving Computation of Square Matrix Norm by
Row-wise/Column-wise 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 .
In this program
OpenMP PARALLEL directive, and CRITICAL section is
used. The CRITICAL directive specifies a region of program that
must be executed by only one thread at a time. If a thread is
currently executing inside a CRITICAL region and another
thread reaches that CRITICAL region and attempts to execute
it, it will block until the first thread exits that CRITICAL
region.
- Input
The suites run for problem sizes - Class A,B,C on 1/2/4/8 threads.
- Output
This Multi Core Benchmark gives the performance of system in terms of
Time , Memory Utilized.
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