Performance optimisation of sequential programs on multi-core processors
- Tristram, Waide B, Bradshaw, Karen
- Authors: Tristram, Waide B , Bradshaw, Karen
- Date: 2012
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/477111 , vital:78046 , ISBN 9781450313087 , https://doi.org/10.1145/2389836.2389851
- Description: With the increasing availability of multi-core processors, the sequential programming paradigm is no longer capable of harnessing the full power of processors. Parallel programming is however, generally complex and requires more expertise than the traditional sequential programming model. On the other hand, there are a multitude of optimisations for sequential programs that can exploit multiple cores without much effort by the programmer. The primary goal of this research is to identify available tools and techniques to aid programmers in the process of optimising C/C++ programs for execution on multi-processors. Using a couple of example programs we show that improved performance is possible using the proposed methodology. However, the choice of optimisation is dependent on the type of problem being solved and there is no generic best choice for all classes of problems.
- Full Text:
- Date Issued: 2012
- Authors: Tristram, Waide B , Bradshaw, Karen
- Date: 2012
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/477111 , vital:78046 , ISBN 9781450313087 , https://doi.org/10.1145/2389836.2389851
- Description: With the increasing availability of multi-core processors, the sequential programming paradigm is no longer capable of harnessing the full power of processors. Parallel programming is however, generally complex and requires more expertise than the traditional sequential programming model. On the other hand, there are a multitude of optimisations for sequential programs that can exploit multiple cores without much effort by the programmer. The primary goal of this research is to identify available tools and techniques to aid programmers in the process of optimising C/C++ programs for execution on multi-processors. Using a couple of example programs we show that improved performance is possible using the proposed methodology. However, the choice of optimisation is dependent on the type of problem being solved and there is no generic best choice for all classes of problems.
- Full Text:
- Date Issued: 2012
Hydra: A Python Framework for Parallel Computing
- Tristram, Waide B, Bradshaw, Karen
- Authors: Tristram, Waide B , Bradshaw, Karen
- Date: 2009
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/477100 , vital:78045 , ISBN 9781607500650 , https://doi.org/10.3233/978-1-60750-065-0-311
- Description: This paper investigates the feasibility of developing a CSP to Python translator using a concurrent framework for Python. The objective of this translation framework, developed under the name of Hydra, is to produce a tool that helps programmers implement concurrent software easily using CSP algorithms. This objective was achieved using the ANTLR compiler generator tool, Python Remote Objects and PyCSP. The resulting Hydra prototype takes an algorithm defined in CSP, parses and converts it to Python and then executes the program using multiple instances of the Python interpreter. Testing has revealed that the Hydra prototype appears to function correctly, allowing simultaneous process execution. Therefore, it can be concluded that converting CSP to Python using a concurrent framework such as Hydra is both possible and adds flexibility to CSP with embedded Python statements.
- Full Text:
- Date Issued: 2009
- Authors: Tristram, Waide B , Bradshaw, Karen
- Date: 2009
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/477100 , vital:78045 , ISBN 9781607500650 , https://doi.org/10.3233/978-1-60750-065-0-311
- Description: This paper investigates the feasibility of developing a CSP to Python translator using a concurrent framework for Python. The objective of this translation framework, developed under the name of Hydra, is to produce a tool that helps programmers implement concurrent software easily using CSP algorithms. This objective was achieved using the ANTLR compiler generator tool, Python Remote Objects and PyCSP. The resulting Hydra prototype takes an algorithm defined in CSP, parses and converts it to Python and then executes the program using multiple instances of the Python interpreter. Testing has revealed that the Hydra prototype appears to function correctly, allowing simultaneous process execution. Therefore, it can be concluded that converting CSP to Python using a concurrent framework such as Hydra is both possible and adds flexibility to CSP with embedded Python statements.
- Full Text:
- Date Issued: 2009
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