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{{Short description|American semiconductor company}}{{Infobox company
| name = Cerebras Systems Inc.
| logo = Cerebras logo.svg
| type = [[Privately held company|Private]]
| image = 1237 E. Arques Avenue.jpg
| image_caption = Headquarters in Sunnyvale
| genre =
| fate =
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| defunct =
| location_city = [[Sunnyvale, California]]
| location_country =
| location =
| locations =
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| production =
| services =
| num_employees = 335 (2023)<ref>{{cite web |last=Takahashi |first=Dean |date=20 July 2023 |title=Cerebras unveils world's largest AI training supercomputer with 54M cores |url=https://venturebeat.com/ai/cerebras-unveils-worlds-larges-ai-training-supercomputer-with-54m-cores/ |website=VentureBeat}}</ref>
| homepage = {{URL|
| footnotes =
| intl =
}}
'''Cerebras Systems Inc.''' is an American [[artificial intelligence]] (AI) company with offices in [[Sunnyvale, California|Sunnyvale]] and [[San Diego]], [[Toronto]], [[Tokyo]]<ref name=":0">{{Cite web|date=2021-04-20|title=Cerebras launches new AI supercomputing processor with 2.6 trillion transistors|url=https://venturebeat.com/2021/04/20/cerebras-systems-launches-new-ai-supercomputing-processor-with-2-6-trillion-transistors/|access-date=2021-04-30|website=VentureBeat|language=en-US}}</ref> and [[Bangalore]], India.<ref name=":18">{{Cite web |title=Cerebras Systems Accelerates Global Growth with New India Office |url=https://finance.yahoo.com/news/cerebras-systems-accelerates-global-growth-004600341.html |access-date=2022-08-30 |website=finance.yahoo.com |language=en-US}}</ref><ref name=":19">{{Cite web |last=Jolly |first=Andrew |title=Cerebras Systems Opens New India Office |url=https://www.hpcwire.com/off-the-wire/cerebras-systems-opens-new-india-office/ |access-date=2022-08-30 |website=HPCwire |language=en-US}}</ref> Cerebras builds computer systems for complex
== History ==
Cerebras was founded in 2015 by Andrew Feldman, Gary Lauterbach, Michael James, Sean Lie and Jean-Philippe Fricker.<ref name=":2">{{Cite web|last=Tilley|first=Aaron|title=AI Chip Boom: This Stealthy AI Hardware Startup Is Worth Almost A Billion|url=https://www.forbes.com/sites/aarontilley/2017/08/31/ai-chip-cerebras-systems-investment/|access-date=2021-04-30|website=Forbes|language=en}}</ref> These five founders worked together at [[SeaMicro]], which was started in 2007 by Feldman and Lauterbach and was later sold to AMD in 2012 for $334 million.<ref>{{Cite web|last=Hardy|first=Quentin|date=2012-02-29|title=A.M.D. Buying SeaMicro for $334 Million|url=https://bits.blogs.nytimes.com/2012/02/29/a-m-d-buying-seamicro-for-334-million/|access-date=2021-04-30|website=Bits Blog|language=en-US}}</ref><ref>{{Cite magazine|title=How Google Spawned The 384-Chip Server|language=en-US|magazine=Wired|url=https://www.wired.com/2012/01/seamicro-and-google/|access-date=2021-04-30|issn=1059-1028}}</ref>
In May 2016, Cerebras secured $27 million in [[series A funding]] led by [[Benchmark (venture capital firm)|Benchmark]], [[Foundation Capital]] and Eclipse Ventures.<ref>{{Cite web|title=A stealthy startup called Cerebras raised around $25 million to build deep learning hardware|url=https://
In December 2016, [[series B funding]] was led by [[Coatue Management|Coatue]], followed in January 2017 with series C funding led by VY Capital.<ref name=":2" />
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In November 2018, Cerebras closed its series D round with $88 million, making the company a [[Unicorn (finance)|unicorn]]. Investors in this round included [[Altimeter Capital|Altimeter]], VY Capital, Coatue, Foundation Capital, Benchmark, and Eclipse.<ref>{{Cite web|last=Martin|first=Dylan|date=2019-11-27|title=AI Chip Startup Cerebras Reveals 'World's Fastest AI Supercomputer'|url=https://www.crn.com/news/components-peripherals/ai-chip-startup-cerebras-systems-raises-88-million-series-d-round|access-date=2021-04-30|website=CRN}}</ref><ref name=":3">{{Cite web|last=Strategy|first=Moor Insights and|title=Cerebras Unveils AI Supercomputer-On-A-Chip|url=https://www.forbes.com/sites/moorinsights/2019/08/19/cerebras-unveils-ai-supercomputer-on-a-chip/|access-date=2021-04-30|website=Forbes|language=en}}</ref>
On August 19, 2019, Cerebras announced its Wafer-Scale Engine (WSE).<ref name=":4">{{Cite news|last=Metz|first=Cade|date=2019-08-19|title=To Power A.I., Start-Up Creates a Giant Computer Chip|language=en-US|work=The New York Times|url=https://www.nytimes.com/2019/08/19/technology/artificial-intelligence-chip-cerebras.html|access-date=2021-04-30|issn=0362-4331}}</ref><ref name=":5">{{Cite web|title=The Cerebras CS-1 computes deep learning AI problems by being bigger, bigger, and bigger than any other chip|url=https://
In November 2019, Cerebras closed its series E round with over $270 million for a valuation of $2.4 billion.<ref>{{Cite news|title=Cerebras Crams More Compute Into Second-Gen 'Dinner Plate Sized' Chip|work=EE Times|url=https://www.eetimes.com/cerebras-crams-more-compute-into-second-gen-dinner-plate-sized-chip/|access-date=2021-05-12}}</ref>
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== Technology ==
The Cerebras Wafer Scale Engine (WSE) is a single, wafer-scale integrated processor that includes compute, memory and [[interconnect fabric]]. The WSE-1 powers the Cerebras CS-1, which is Cerebras’ first-generation AI computer.<ref name=":7">{{Cite web|title=Full Page Reload|url=https://spectrum.ieee.org
The WSE-1 has 1.2 trillion transistors, 400,000 compute cores and 18 gigabytes of memory.<ref name=":4" /><ref name=":5" /><ref name=":6" />
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In September 2022, Cerebras announced that it can patch its chips together to create what would be the largest-ever computing cluster for AI computing.<ref name=":20">{{Cite web |last=Shah |first=Agam |date=2022-09-14 |title=Cerebras Proposes AI Megacluster with Billions of AI Compute Cores |url=https://www.hpcwire.com/2022/09/14/cerebras-proposes-ai-megacluster-with-billions-of-ai-compute-cores/ |access-date=2022-09-14 |website=HPCwire |language=en-US}}</ref> A Wafer-Scale Cluster can connect up to 192 CS-2 AI systems into a cluster, while a cluster of 16 CS-2 AI systems can create a computing system with 13.6 million cores for natural language processing.<ref name=":20" /> The key to the new Cerebras Wafer-Scale Cluster is the exclusive use of data parallelism to train, which is the preferred approach for all AI work.<ref>{{Cite web |last=Freund |first=Karl |title=New Cerebras Wafer-Scale Cluster Eliminates Months Of Painstaking Work To Build Massive Intelligence |url=https://www.forbes.com/sites/karlfreund/2022/09/14/new-cerebras-wafer-scale-cluster-eliminates-months-of-painstaking-work-to-build-massive-intelligence/ |access-date=2022-09-15 |website=Forbes |language=en}}</ref>
In November 2022, Cerebras unveiled its latest supercomputer, Andromeda, which combines 16 WSE-2 chips into one cluster with 13.5 million AI-optimized cores, delivering up to 1 Exaflop of AI computing horsepower, or at least one quintillion (10 to the power of 18) operations per second.<ref name=":21">{{Cite web |
In November 2022, Cerebras announced its partnership with [[Cirrascale Cloud Services]] to provide a flat-rate "pay-per-model" compute time for its ''Cerebras AI Model Studio''. Pricing ranges from $2,500 for training "a 1.3-billion-parameter model of GPT-3 in 10 hours" to $2.5 million for training "70-billion-parameter version in 85 days". The service is said to reduce the cost—compared to the similar cloud services on the market—by half while increasing speed up to eight times faster.<ref>{{Cite web |url=https://www.zdnet.com/article/ai-challenger-cerebras-unveils-pay-per-model-large-model-ai-cloud-service-with-cirrascale-jasper/ |title=AI challenger Cerebras unveils 'pay-per-model' AI cloud service with Cirrascale, Jasper |last=Ray |first=Tiernan |date=2022-11-29 |work=ZDNet}}</ref>
In 2024 the company introduced WSE-3, a 5nm-based chip hosting 4 trillion transistors and 900,000 AI-optimized cores, the basis of the CS-3 computer along with a collaboration with [[Dell Technologies]].<ref>{{Cite web |last=Kuka |first=Valeriia |last2=Se |first2=Ksenia |date=June 15, 2024 |title=Cerebras: an Engineering Marvel to Rival NVIDIA |url=https://www.turingpost.com/p/cerebras |access-date=2024-06-15 |website=Turing Post |language=en}}</ref>
== Deployments ==
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Customers are reportedly using Cerebras technologies in the pharmaceutical, life sciences, and energy sectors.<ref name=":9">{{Cite web|date=2020-10-13|title=LLNL, ANL and GSK Provide Early Glimpse into Cerebras AI System Performance|url=https://www.hpcwire.com/2020/10/13/llnl-anl-and-gsk-provide-early-glimpse-into-cerebras-ai-system-performance/|access-date=2021-06-03|website=HPCwire|language=en-US}}</ref><ref name=":14">{{Cite web |date=2022-03-03 |title=Cerebras Systems Supplies 2nd-Gen AI System to TotalEnergies |url=https://www.enterpriseai.news/2022/03/03/cerebras-systems-supplies-2nd-gen-ai-system-to-totalenergies/ |access-date=2022-03-04 |website=EnterpriseAI |language=en-US}}</ref>
=== CS-1 ===
In 2020, [[GlaxoSmithKline]] (GSK) began using the Cerebras CS-1 AI system in their London AI hub, for neural network models to accelerate genetic and genomic research and reduce the time taken in [[drug discovery]].<ref>{{Cite web|last=Ray|first=Tiernan|title=Glaxo's biology research with novel Cerebras machine shows hardware may change how AI is done |url= https://www.zdnet.com/article/glaxos-biology-research-with-novel-cerebras-machine-shows-hardware-may-change-how-ai-is-done/ |date= September 5, 2020 |access-date= August 13, 2021 |website= ZDNet|language=en}}</ref> The GSK research team was able to increase the complexity of the encoder models they could generate, while reducing training time.<ref>{{Cite web|title=Cerebras debuts new 2.6 trillion transistor wafer scale chip for AI|url=https://www.datacenterdynamics.com/en/news/cerebras-debuts-new-26-trillion-wafer-scale-chip-for-ai/|access-date=2021-06-17|website=www.datacenterdynamics.com|language=en}}</ref> Other pharmaceutical industry customers include [[AstraZeneca]], who was able to reduce training time from two weeks on a cluster of GPUs to two days using the Cerebras CS-1 system.<ref>{{Cite web|last=Hansen|first=Lars Lynne|date=2021-04-26|title=Accelerating Drug Discovery Research with New AI Models: a look at the AstraZeneca Cerebras…|url=https://larslynnehansen.medium.com/accelerating-drug-discovery-research-with-new-ai-models-a-look-at-the-astrazeneca-cerebras-b72664d8783|access-date=2021-06-03|website=Medium|language=en}}</ref> GSK and Cerebras recently co-published [https://arxiv.org/pdf/2112.07571.pdf research] in December 2021 on epigenomic language models.
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In August 2021, Cerebras announced a partnership with [https://www.peptilogics.com Peptilogics] on the development of AI for [[peptide therapeutics]].<ref>{{Cite web|title=Peptilogics and Cerebras Systems Partner on AI Solutions to Advance Peptide Therapeutics|url=https://www.hpcwire.com/off-the-wire/peptilogics-and-cerebras-systems-partner-on-ai-solutions-to-advance-peptide-therapeutics/|access-date=2021-09-22|website=HPCwire |language=en-US}}</ref>
=== CS-2 ===
In March 2022, Cerebras announced that the Company deployed its CS-2 system in the Houston facilities of [[TotalEnergies]], its first publicly disclosed customer in the energy sector.<ref name=":14" /> Cerebras also announced that it has deployed a CS-2 system at [https://nference.com nference], a startup that uses natural language processing to analyze massive amounts of biomedical data. The CS-2 will be used to train transformer models that are designed to process information from piles of unstructured medical data to provide fresh insights to doctors and improve patient recovery and treatment.<ref>{{Cite web |title=Cerebras brings CS-2 system to data analysis biz nference |url=https://www.theregister.com/2022/03/14/cerebras_ai_chips/ |access-date=2022-03-15 |website=www.theregister.com |language=en}}</ref>
In May 2022, Cerebras announced that the [[National Center for Supercomputing Applications]] (NCSA) has deployed the Cerebras CS-2 system in their HOLL-I supercomputer.
In October 2022, it was announced that the U.S. National Nuclear Security Administration would sponsor a study to investigate using Cerebras' CS-2 in nuclear stockpile stewardship computing.<ref name=":22">{{Cite web |date=2022-10-18 |title=NNSA Taps 3 Federal Labs to Research Applications of Cerebras Systems Tech - ExecutiveBiz |url=https://blog.executivebiz.com/2022/10/nnsa-taps-3-federal-labs-to-research-applications-of-cerebras-systems-tech/ |access-date=2022-11-18 |website=blog.executivebiz.com |language=en-US}}</ref><ref>{{Cite web |last=Mann |first=Tobias |title=DoE to trial Cerebras AI compute in nuclear weapon sims |url=https://www.theregister.com/2022/10/18/doe_cerebras_waferscale/ |access-date=2022-11-18 |website=www.theregister.com |language=en}}</ref> The multi-year contract will be executed through [[Sandia National Laboratories]], [[Lawrence Livermore National Laboratory|Lawrence Livermore National Lab]], and [[Los Alamos National Laboratory]].<ref name=":22" />
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In November 2022, Cerebras and the [[National Energy Technology Laboratory]] (NETL) saw record-breaking performance on the scientific compute workload of forming and solving field equations. Cerebras demonstrated that its CS-2 system was as much as 470 times faster than NETL's Joule Supercomputer in field equation modeling.<ref>{{Cite web |title=Cerebras and National Energy Tech Lab Set New Milestones for High-Performance, Energy-Efficient Field Equation Modeling Using Simple Python Interface |url=https://www.hpcwire.com/off-the-wire/cerebras-and-national-energy-tech-lab-set-new-milestones-for-high-performance-energy-efficient-field-equation-modeling-using-simple-python-interface/ |access-date=2022-11-18 |website=HPCwire |language=en-US}}</ref>
The 2022 Gordon Bell Special Prize Winner for HPC-Based COVID-19 Research, which honors outstanding research achievement towards the understanding of the COVID-19 pandemic through the use of high-performance computing, used Cerebras' CS-2 system to conduct this award-winning research to transform large language models to analyze COVID-19 variants. The paper was authored by a 34-person team from Argonne National Laboratory, California Institute of Technology, Harvard University, Northern Illinois University, Technical University of Munich, University of Chicago, University of Illinois Chicago, Nvidia, and Cerebras. ANL noted that using the CS-2 Wafer-Scale Engine cluster, the team was able to achieve convergence when training on the full SARS-CoV-2 genomes in less than a day.<ref>{{Cite web |last=Peckham |first=Oliver |date=2022-11-17 |title=Gordon Bell Nominee Used LLMs, HPC, Cerebras CS-2 to Predict Covid Variants |url=https://www.hpcwire.com/2022/11/17/gordon-bell-nominee-used-llms-hpc-cerebras-cs-2-to-predict-covid-variants/ |access-date=2022-11-23 |website=HPCwire |language=en-US}}</ref><ref>{{Cite web |last=Peckham |first=Oliver |date=2022-11-17 |title=Gordon Bell Special Prize Goes to LLM-Based Covid Variant Prediction |url=https://www.hpcwire.com/2022/11/17/gordon-bell-special-prize-goes-to-llm-based-covid-variant-prediction/ |access-date=2022-11-23 |website=HPCwire |language=en-US}}</ref>
Cerebras partnered with Emirati technology group [[G42 (company)|G42]] to deploy its AI supercomputers to create chatbots and to analyze genomic and preventive care data. In July 2023, G42 agreed to pay around $100 million to purchase the first of potentially nine supercomputers from Cerebras, each of which capable of 4 [[FLOPS|exaflops]] of compute.<ref>{{cite news |last=Nellis |first=Stephen |last2=Hu |first2=Krystal |date=20 July 2023 |title=Cerebras Systems signs $100 mln AI supercomputer deal with UAE's G42 |url=https://www.reuters.com/technology/cerebras-systems-signs-100-mln-ai-supercomputer-deal-with-uaes-g42-2023-07-20/ |publisher=Reuters}}</ref><ref>{{cite news |last=Lu |first=Yiwen |date=20 July 2023 |title=An A.I. Supercomputer Whirs to Life, Powered by Giant Computer Chips |url=https://www.nytimes.com/2023/07/20/technology/an-ai-supercomputer-whirs-to-life-powered-by-giant-computer-chips.html |work=The New York Times}}</ref><ref>{{cite web |last=Moore |first=Samuel K. |date=20 July 2023 |title=Cerebras Introduces Its 2-Exaflop AI Supercomputer |url=https://spectrum.ieee.org/ai-supercomputer-2662304872 |work=IEEE Spectrum}}</ref> In August 2023, Cerebras, the [[Mohamed bin Zayed University of Artificial Intelligence]] and G42 subsidiary Inception launched [[Jais (language model)|Jais]], a [[large language model]].<ref name=":02">{{Cite news |last=Cherney |first=Max A. |date=2023-08-30 |title=UAE's G42 launches open source Arabic language AI model |language=en |work=[[Reuters]] |url=https://www.reuters.com/technology/uaes-g42-launches-open-source-arabic-language-ai-model-2023-08-30/ |access-date=2023-10-08}}</ref>
[[Mayo Clinic]] announced a collaboration with Cerebra’s at the 2024 [[J.P. Morgan & Co.|J.P. Morgan Healthcare Conference]], offering details on the first foundation model it will develop with the enablement of Cerebras's generative AI computing capability. The solution will combine genomic data with de-identified data from patient records and medical evidence to explore the ability to predict a patient's response to treatments to manage disease and will initially be applied to [[rheumatoid arthritis]]. The model could serve as a prototype for similar solutions to support the diagnosis and treatment of other diseases.
== See also ==
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[[Category:Companies based in Sunnyvale, California]]
[[Category:Companies based in Silicon Valley]]
[[Category:Computer hardware companies]]
[[Category:Semiconductor companies of the United States]]
[[Category:Fabless semiconductor companies]]
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