![]() ![]() In October 2016 several OpenPOWER partners formed the OpenCAPI Consortium together with GPU and CPU designer AMD and systems designers Dell EMC and Hewlett Packard Enterprise to spread the technology beyond the scope of OpenPOWER and IBM. At the same time, IBM and several other companies founded the OpenPOWER Foundation to build an ecosystem around Power based technologies, including CAPI. It was designed by IBM for use in its POWER8 based systems which came to market in 2014. Memory intensive and computation intensive works like matrix multiplications for deep neural networks can be offloaded into CAPI-supported platforms. Especially in the datacenter, improving the interconnect became paramount in moving toward a heterogeneous architecture in which hardware becomes increasingly tailored to specific compute workloads.ĬAPI was developed to enable computers to more easily and efficiently attach specialized accelerators. In many applications, accelerators struggle with limitations of the interconnect's performance (bandwidth and latency) or with limitations due to the interconnect's architecture (such as lacking memory coherence). Where large performance gains have been realized, it was often associated with increasingly specialized compute units, such as GPU units added to the processor die, or external GPU- or FPGA-based accelerators. Over the decade that followed, few commercial CPU products exceeded 4 GHz, with the majority of performance improvements now coming from incrementally improved microarchitectures, better systems integration, and higher compute density-this largely in the form of packing a larger numbers of independent cores onto the same die, often at the expense of peak operating frequency (Intel's 24-core Xeon E7-8890 from June 2016 has a base operating frequency of just 2.2 GHz, so as to operate within the constraints of a single-socket 165 W power consumption and cooling budget). Here both projects ran into a thermal scaling wall, whereby heat extraction problems associated with further increases in operating frequency largely outweighed gains from shorter cycle times. This process is experimental and the keywords may be updated as the learning algorithm improves.The performance scaling traditionally associated with Moore's Law-dating back to 1965-began to taper off around 2004, as both Intel's Prescott architecture and IBM's Cell processor pushed toward a 4 GHz operating frequency. These keywords were added by machine and not by the authors. An example of such a general purpose embedded processor is LSI Logic’s CW4001, which is based on the MIPS family of processors. Apart from the processors in the Digital Signal Processing domain (such as the TMS320 series from Texas Instruments), we also find microprocessors with relatively general purpose architectures available as embedded processors. This is feasible in current technology due to the relatively small area occupied by the processor cores, making the rest of the on-chip die area available for RAM, ROM, coprocessors, and other modules. The software part of the partitioned specification of Figure 1.2 is executed on these embedded processors, which are often available in the form of cores, to be instantiated as part of a larger system on a chip. ![]() Modern embedded systems increasingly rely on processors due to the advantages they offer in terms of flexibility, reduction in design time and full-custom layout quality. ![]()
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