Manycore processor

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Short description: Multi-core processor with a large number of cores

Manycore processors are special kinds of multi-core processors designed for a high degree of parallel processing, containing numerous simpler, independent processor cores (from a few tens of cores to thousands or more). Manycore processors are used extensively in embedded computers and high-performance computing.

Contrast with multicore architecture

Manycore processors are distinct from multi-core processors in being optimized from the outset for a higher degree of explicit parallelism, and for higher throughput (or lower power consumption) at the expense of latency and lower single-thread performance.

The broader category of multi-core processors, by contrast, are usually designed to efficiently run both parallel and serial code, and therefore place more emphasis on high single-thread performance (e.g. devoting more silicon to out-of-order execution, deeper pipelines, more superscalar execution units, and larger, more general caches), and shared memory. These techniques devote runtime resources toward figuring out implicit parallelism in a single thread. They are used in systems where they have evolved continuously (with backward compatibility) from single core processors. They usually have a 'few' cores (e.g. 2, 4, 8) and may be complemented by a manycore accelerator (such as a GPU) in a heterogeneous system.

Motivation

Cache coherency is an issue limiting the scaling of multicore processors. Manycore processors may bypass this with methods such as message passing,[1] scratchpad memory, DMA,[2] partitioned global address space,[3] or read-only/non-coherent caches. A manycore processor using a network on a chip and local memories gives software the opportunity to explicitly optimise the spatial layout of tasks (e.g. as seen in tooling developed for TrueNorth).[4]

Manycore processors may have more in common (conceptually) with technologies originating in high-performance computing such as clusters and vector processors.[5]

GPUs may be considered a form of manycore processor having multiple shader processing units, and only being suitable for highly parallel code (high throughput, but extremely poor single thread performance).

Suitable programming models

Classes of manycore systems

Specific manycore architectures

  • ZettaScaler [1], Japanese PEZY Computing 2,048-core modules
  • Xeon Phi coprocessor, which has MIC (Many Integrated Cores) architecture
  • Tilera
  • Adapteva Epiphany Architecture, a manycore chip using PGAS scratchpad memory
  • Coherent Logix hx3100 Processor, a 100-core DSP/GPP processor based on HyperX Architecture
  • Movidius Myriad 2, a manycore vision processing unit (VPU)
  • Kalray, a manycore PCI-e accelerator for data-intensive tasks
  • Teraflops Research Chip, a manycore processor using message passing
  • TrueNorth, an AI accelerator with a manycore network on a chip architecture
  • Green arrays, a manycore processor using message passing aimed at low power applications
  • Sunway SW26010, a 260-core manycore processor used in the then top 1 supercomputer Sunway TaihuLight
    • SW52020, an improved 520-core[8][9] variant of SW26010, with 512-bit SIMD (also adding support for half-precision), used in a prototype, meant for an exascale system (and in the future 10 exascale system), and according to datacenterdynamics China is rumored to already have two separate exascale systems secretly[citation needed]
  • Eyeriss, a manycore processor designed for running convolutional neural nets for embedded vision applications[10]
  • Graphcore, a manycore AI accelerator

Specific manycore computers with 1M+ CPU cores

A number of computers built from multicore processors have one million or more individual CPU cores. Examples include:

Specific computers with 5 million or more CPU cores

Quite a few supercomputers have over 5 million CPU cores. When there are also coprocessors, e.g. GPUs used with, then those cores are not listed in the core-count, then quite a few more computers would hit those targets.

  • Frontier
  • Fugaku, a Japanese supercomputer using Fujitsu A64FX ARM-based cores, 7,630,848 in total.
  • Sunway TaihuLight, a massively parallel (10 million CPU cores) Chinese supercomputer, once one of the fastest supercomputers in the world, using a custom manycore architecture.[citation needed] As of November 2018, it was the world's third fastest supercomputer (as ranked by the TOP500 list), obtaining its performance from 40,960 SW26010 manycore processors, each containing 256 cores.

See also

References

  1. Mattson, Tim (January 2010). "The Future of Many Core Computing: A tale of two processors". https://cseweb.ucsd.edu/classes/fa12/cse291-c/talks/SCC-80-core-cern.pdf. 
  2. Hendry, Gilbert; Kretschmann, Mark. "IBM Cell Processor". http://meseec.ce.rit.edu/756-projects/spring2006/d2/6/cell-architecture-final.pdf. 
  3. Olofsson, Andreas; Nordström, Tomas; Ul-Abdin, Zain (2014). "Kickstarting High-performance Energy-efficient Manycore Architectures with Epiphany". arXiv:1412.5538 [cs.AR].
  4. Amir, Arnon (June 11, 2015). "IBM SyNAPSE Deep Dive Part 3". IBM Research. https://www.youtube.com/watch?v=6O6igM4lMDc. 
  5. "cell architecture". http://www.blachford.info/computer/Cell/Cell1_v2.html. "The Cell architecture is like nothing we have ever seen in commodity microprocessors, it is closer in design to multiprocessor vector supercomputers"
  6. Rick Merritt (June 20, 2011), "OEMs show systems with Intel MIC chips", www.eetimes.com (EE Times), http://www.eetimes.com/electronics-news/4217092/OEMs-show-systems-with-Intel-MIC-chips 
  7. Barker, J; Bowden, J (2013). "Manycore Parallelism through OpenMP". IWOMP. Springer. doi:10.1007/978-3-642-40698-0_4. 
  8. Morgan, Timothy Prickett (2021-02-10). "A First Peek At China's Sunway Exascale Supercomputer" (in en-US). http://www.nextplatform.com/2021/02/10/a-sneak-peek-at-chinas-sunway-exascale-supercomputer/. 
  9. Hemsoth, Nicole (2021-04-19). "China's Exascale Prototype Supercomputer Tests AI Workloads" (in en-US). http://www.nextplatform.com/2021/04/19/chinas-exascale-prototype-supercomputer-tests-ai-workloads/. 
  10. "Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks". IEEE International Solid-State Circuits Conference, ISSCC 2016, Digest of Technical Papers. 2016. pp. 262–263. https://www.mit.edu/~sze/eyeriss.html. 

External links