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Software architecture and system validation of an open, unified model for accelerated multicore computing.

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Title: Software architecture and system validation of an open, unified model for accelerated multicore computing.
Authors: Crawford, C. H.1 catcraw@us.ibm.com, Burdick, D. J.2 deanburdick@us.ibm.com, Dale, J. N.1 jndale@us.ibm.com, Ford, E. F.3 egan@us.ibm.com, Mikosh, R. A.1 mikosh@us.ibm.com, Nobles, A.4 aenobles@us.ibm.com, To, V.1 vto@us.ibm.com
Source: IBM Journal of Research & Development. Sep2009, Vol. 53 Issue 5, p6:1-6:12. 12p.
Subjects: IBM Systems Application Architecture, IBM software, International Business Machines Corp., Multicore processors, Hybrid computers (Computer architecture), Software validation, Workload of computer networks, Microprocessor programming
Abstract: For systems that use hardware accelerators to combine multicore and multiprocess technology with libraries and computational kernels, the drawbacks are the complexity of the programming model and the corresponding verification of the software and validation of the system performance capabilities. In this paper, we describe a software approach to utilizing the compute power of the Cell Broadband Enginet processor and a cluster composed of x86-64 and IBM PowerXCelle 8i processors integrated within a single hybrid compute node. We review past approaches to provide motivation for our development of the Data Communication and Synchronization (DaCS) library and Accelerated Library Framework (ALF), which enable developers to create new applications and adapt existing applications to exploit hybrid computing platforms. We follow with examples of porting existing x86-64 processor-based applications to the hybrid cluster platform in order to demonstrate the capabilities of ALF and DaCS and discuss how one application was extended to become a stress and performance test for various system components. Finally, we present the applicability of this programming model, accelerator design, and test architecture to other system architectures, applications, and workload segments. [ABSTRACT FROM AUTHOR]
Copyright of IBM Journal of Research & Development is the property of IBM Corporation/IBM Journals and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 47838430
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: For systems that use hardware accelerators to combine multicore and multiprocess technology with libraries and computational kernels, the drawbacks are the complexity of the programming model and the corresponding verification of the software and validation of the system performance capabilities. In this paper, we describe a software approach to utilizing the compute power of the Cell Broadband Enginet processor and a cluster composed of x86-64 and IBM PowerXCelle 8i processors integrated within a single hybrid compute node. We review past approaches to provide motivation for our development of the Data Communication and Synchronization (DaCS) library and Accelerated Library Framework (ALF), which enable developers to create new applications and adapt existing applications to exploit hybrid computing platforms. We follow with examples of porting existing x86-64 processor-based applications to the hybrid cluster platform in order to demonstrate the capabilities of ALF and DaCS and discuss how one application was extended to become a stress and performance test for various system components. Finally, we present the applicability of this programming model, accelerator design, and test architecture to other system architectures, applications, and workload segments. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IBM Journal of Research & Development is the property of IBM Corporation/IBM Journals and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1147/JRD.2009.5429072
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              Text: Sep2009
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