Cell software development: Difference between revisions

Revision as of 14:39, 30 August 2018

Revision as of 02:49, 9 February 2019

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==Linux on Cell==

An open source software-based strategy was adopted to accelerate the development of a Cell BE ecosystem and to provide an environment to develop Cell applications, including a GCC-based Cell compiler, binutils and a port of the Linux operating system.<ref name="research.ibm.com">{{cite web|url=http://www.research.ibm.com/people/m/mikeg/papers/2007_ieeecomputer.pdf|format=PDF|title=An Open Source Environment for Cell Broadband Engine System Software|date=June 2007}}</ref>

==Octopiler==

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Transferring data between the local stores of different SPUs can have a large performance cost. The local stores of individual SPUs can be exploited using a variety of strategies.

Applications with high locality, such as dense matrix computations, represent an ideal workload class for the local stores in Cell BE.<ref>{{cite web|url=http://www.research.ibm.com/people/m/mikeg/papers/2006_ieeemicro.pdf|format=PDF|title=Synergistic Processing in Cell's Multicore Architecture|date=March 2006}}</ref>

Streaming computations can be efficiently accommodated using [[software pipelining]] of memory block transfers using a multi-buffering strategy.<ref name="research.ibm.com"/>

The software cache offers a solution for random accesses.<ref>{{cite web|url=http://www.research.ibm.com/journal/sj/451/eichenberger.pdf|format=PDF|title=Using advanced compiler technology to exploit the performance of the Cell Broadband Engine architecture|date=January 2006}}</ref>

More sophisticated applications can use multiple strategies for different data types.<ref>{{cite web|url=http://www.research.ibm.com/cell/papers/2008_vee_cellgc.pdf|format=PDF|title=Cell GC: Using the Cell Synergistic Processor as a Garbage Collection Coprocessor |date=March 2008}}</ref>

===References===