| 1. |
- Dastgeer, Usman, 1986-
(författare)
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Performance-aware Component Composition for GPU-based systems
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis addresses issues associated with efficiently programming modern heterogeneous GPU-based systems, containing multicore CPUs and one or more programmable Graphics Processing Units (GPUs). We use ideas from component-based programming to address programming, performance and portability issues of these heterogeneous systems. Specifically, we present three approaches that all use the idea of having multiple implementations for each computation; performance is achieved/retained either a) by selecting a suitable implementation for each computation on a given platform or b) by dividing the computation work across different implementations running on CPU and GPU devices in parallel.In the first approach, we work on a skeleton programming library (SkePU) that provides high-level abstraction while making intelligent implementation selection decisions underneath either before or during the actual program execution. In the second approach, we develop a composition tool that parses extra information (metadata) from XML files, makes certain decisions online, and, in the end, generates code for making the final decisions at runtime. The third approach is a framework that uses source-code annotations and program analysis to generate code for the runtime library to make the selection decision at runtime. With a generic performance modeling API alongside program analysis capabilities, it supports online tuning as well as complex program transformations.These approaches differ in terms of genericity, intrusiveness, capabilities and knowledge about the program source-code; however, they all demonstrate usefulness of component programming techniques for programming GPU-based systems. With experimental evaluation, we demonstrate how all three approaches, although different in their own way, provide good performance on different GPU-based systems for a variety of applications.
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| 2. |
- Jackson, Adrian, et al.
(författare)
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High Performance I/O
- 2011
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Ingår i: Parallel, Distributed and Network-Based Processing (PDP), 2011 19th Euromicro International Conference on. - 9781424496822 ; , s. 349-356
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Konferensbidrag (refereegranskat)abstract
- Parallelisation, serial optimisation, compiler tuning, and many more techniques are used to optimise and improve the performance scaling of parallel programs. One area which is frequently not optimised is file I/O. This is because it is often not considered to be key to the performance of a program and also because it is traditionally difficult to optimise and very machine specific. However, in the current era of Peta- and Exascale computing it is no longer possible to ignore I/O performance as it can significantly limit the scaling of many codes when executing on very large numbers of processors or cores. Furthermore, as producing data is the main purpose of most simulation codes any work that can be undertaken to provide improved performance of I/0 can be applicable to a very large range of simulation codes, and provide them with improved functionality (i.e. the ability to produce more data).This paper describes some of the issues surrounding I/O, the technology that is commonly deployed to provide I/O on HPC machines and the software libraries available to programmers to undertake I/O. The performance of all these aspects of I/O on a range of HPC systems were investigated by the authors and a represented in this paper to motivate the discussions in the paper.
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| 3. |
- Jackson, Adrian, et al.
(författare)
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Parallel Optimisation Strategies for Fusion Codes
- 2011
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Ingår i: Parallel, Distributed and Network-Based Processing (PDP), 2011 19th Euromicro International Conference on. - 9781424496822 ; , s. 357-364
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Konferensbidrag (refereegranskat)abstract
- We have previously documented the on-going work in the EUFORIA project to parallelise and optimise European fusion simulation codes, see. This involves working with a wide range of codes to try and address any performance and scaling issues that these codes have. However, as no two simulation codes are exactly the same, it is very hard to apply exactly the same approach to optimising a disparate range of codes. Indeed, it can be seen from that the codes investigated range in terms of performance and ability from well-optimised, highly parallelised codes, to serial or poorly performing codes. After analysing, optimising, and parallelising a range of codes it is, actually, possible to discern a number of distinct optimisation techniques or approaches/strategies that can be used to improve the performance or scaling of a parallel simulation code. This paper outlines the distinct approaches that we have identified, highlighting their benefits and drawbacks, giving an overview of the type of work that is often attempted for fusion simulation code optimisation.
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| 4. |
- Schwiegelshohn, Uwe, et al.
(författare)
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Perspectives on grid computing
- 2010
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Ingår i: Future generations computer systems. - : Elsevier BV. - 0167-739X .- 1872-7115. ; 26:8, s. 1104-1115
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Tidskriftsartikel (refereegranskat)abstract
- Grid computing has been the subject of many large national and international IT projects. However, not all goals of these projects have been achieved. In particular. the number of users lags behind the initial forecasts laid out by proponents of grid technologies. This underachievement may have led to claims that the grid concept as a whole is on its way to being replaced by Cloud computing and various X-as-a-Service approaches. In this paper, we try to analyze the current situation and to identify promising directions for future grid development. Although there are shortcomings in current grid systems, we are convinced that the concept as a whole remains valid and can benefit from new developments, including Cloud computing. Furthermore, we strongly believe that some future applications will require the grid approach and that, as a result, further research is required in order to turn this concept into reliable, efficient and user-friendly computing platforms. (c) 2010 Elsevier B.V. All rights reserved.
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