Performance gains when multicore partners with AdvancedTCA

The AdvancedTCA infrastructure works well for supporting multicore processors, an integral element of electronics design.

In recent years processor technology has changed its focus. Instead of increasing processor clock rate it is adding more and more processor cores. Combining this silicon development direction with AdvancedTCA form factor results in multi-level performance scaling options. Performance can be scaled by using processor silicon devices that have more processor cores and by adding more AdvancedTCA blades into the chassis. Moreover, AdvancedTCA systems can be tailor scaled for a specific workload by combining standard multicore x86 processors with more specialized Packet Processors. Here Gene explores such AdvancedTCA system creation options and the performance gains they offer.

Today, multicore processors are an integral element of electronics design and are well supported by the AdvancedTCA infrastructure. AdvancedTCA enables very high compute density, without sacrificing reliability and redundancy. Redundant high-speed chassis-wide interconnect options support high-performance computing clusters as well as high-performance communication applications. Load balancing and policy routing techniques enable packet distribution among the blades, avoiding bottlenecks and fully utilizing multicore devices. Although most legacy applications can’t take advantage of multicore performance, software techniques such as virtualization let multiple legacy applications run on the same processor, taking full advantage of the available multiple cores. Finally, software tools and hardware offload elements ease new application development or existing application porting to multicore environments.

Gene Juknevicius is Senior Architect & Technologist, GE Intelligent Platforms. He has participated in the PICMG, AMC, and MicroTCA committees, is currently an active member of the SCOPE Alliance and is responsible for new product definition and architecture at GE Intelligent Platforms. He received his M.S. degree in Electrical Engineering from Stanford University.

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