PRESS RELEASE

Wave Computing acquires MIPS

Wave Computing has announced that it has acquired MIPS Tech, (formerly MIPS Technologies), a specialist in RISC processor Intellectual Property (IP) and licensable CPU cores.

The acquisition will accelerate Wave’s strategy of offering AI acceleration from the datacentre to the ‘edge of cloud’ by extending the company’s products beyond AI systems to now also include AI-enabled embedded solutions.

Recent estimates from market research firm Tractica show a $50B TAM for AI solutions targeting the datacentre and on-premise environments, and a $100B TAM for AI solutions at the edge of cloud.

However, data scientists continue to struggle with the poor performance and lack of scalability of legacy compute architectures, which must be obtained from multiple sources, while trying to serve varying use cases. For example, datacentre-centric AI applications today need many weeks to train using coprocessors such as GPUs, only to require a different architecture for inferencing at the Edge. The lack of a common AI platform, from datacentre to edge, slows market growth and reduces productivity of data scientists in fields such as autonomously driven vehicles, IoT sensors and more.

Dado Banatao, Chairman of Wave Computing and MIPS Technologies, said, ‘Now is the right time for Wave Computing to expand, and I am pleased to see the company further evolve and grow into an AI powerhouse. Wave’s integration of two industry-leading compute architectures in a single data plane/control plane solution – Dataflow and Von Neumann – will be truly unique and an industry-first. It will fuel new, ground-breaking innovations in AI and other fields.’

‘This is a major milestone not only in the history of our two companies, but also for the AI compute industry,’ said Derek Meyer, CEO of Wave Computing. ‘With working DPU commercial silicon and being in the final stages of bringing our first AI systems to market, now is the time for us to expand to the edge of cloud. The acquisition of MIPS allows us to combine technologies to create products that will deliver a single ‘Datacenter-to-Edge’ platform ideal for AI and deep learning. We’ve already received very strong and enthusiastic support from leading suppliers and strategic partners, as they affirm the value of data scientists being able to experiment, develop, test and deploy their neural networks on a common platform spanning to the edge of cloud.’

Alexander Stojanovic, vice president of machine learning and applied research at eBay, said, ‘For AI-driven Datacenters, leveraging purpose-built platforms for high throughput and low latency workloads is a game changer. They offer the promise of faster time-to-revenue and greater competitive differentiation using some of the latest AI trends such as GAN and attention-based models for time series and natural language data. Combined with the ability to more quickly create deeper and more complex machine learning models, hyperscale- and enterprise-class companies will be able to better leverage AI as a fundamental part of their digital strategies.’

Ben Bajarin, Principal Analyst at Creative Strategies, said, ‘As a long-time supporter of the MIPS architecture, I’ve believed in the unique value of its technology, which spans 64-bit to multi-threading capabilities. The combination of the MIPS architecture with Wave Computing’s dataflow technology in a single solution will create a compelling offering for the AI industry, and benefit developers from the cloud to the edge.’

Kiran Kumar, technology analyst at Frost & Sullivan, said, ‘Wave Computing is among the first of the AI startup companies to expand its operations through an acquisition. With the addition of MIPS, Wave can speed its drive to the Edge of Cloud and expand its market opportunities. This effort is an example of why Frost awarded Wave the Technology Innovation Leader Award for the Machine Learning Industry in 2018. We look forward to Wave’s additional progress and growth.’

Karl Freund, lead analyst for HPC and deep learning at Moor Insights & Strategy, said, ‘The acquisition of MIPS by Wave Computing is a bold move, and could accelerate its time to profitability and industry presence. By adding new IP to Wave’s dataflow-centric portfolio, the company has positioned itself as a much broader player in AI.’

Rich Wawrzyniak, principal analyst at Semico Research, said, ‘I am pleased to see MIPS be adopted by one of the world’s most advanced AI technology companies. Not only does this acquisition bolster Wave Computing’s existing dataflow portfolio, it provides the MIPS team a solid foundation from which to grow under the capable leadership of MIPS veterans and AI leaders. This is a brilliant move.’

Kevin Krewell, principal analyst at TIRIAS Research, said, ‘The combination of Wave Computing with MIPS offers the promise to AI developers of a single platform that can scale from IoT Edge nodes to Datacenters. This is a bold and strategic move by Wave to further its position among their AI startup peer group.’

Anand Joshi, principal analyst at Tractica, said, ‘The market opportunity for AI is exploding, specifically in Edge applications such as the Automotive, Retail, IoT, Consumer and Manufacturing segments. With this acquisition, Wave Computing is now one of the few AI technology providers to span both ends of the AI spectrum.’

The MIPS acquisition is both cash flow positive and accretive to Wave Computing. As a combined entity under the name Wave Computing, MIPS will operate as an IP business unit and continue to license MIPS IP solutions that can now integrate Wave’s dataflow technology. With over 350 worldwide patents and 200 licensees, the MIPS acquisition strengthens Wave’s global presence and IP portfolio. With MIPS, Wave Computing will be able to provide the industry’s broadest set of high-performance, high-efficiency training and inferencing compute solutions that scale across virtually all form factors and AI implementations.

Greenhill & Co. is serving as financial advisor to Wave Computing.

Company: 
Other tags: 
Feature

Robert Roe reports on developments in AI that are helping to shape the future of high performance computing technology at the International Supercomputing Conference

Feature

James Reinders is a parallel programming and HPC expert with more than 27 years’ experience working for Intel until his retirement in 2017. In this article Reinders gives his take on the use of roofline estimation as a tool for code optimisation in HPC

Feature

Sophia Ktori concludes her two-part series exploring the use of laboratory informatics software in regulated industries.

Feature

As storage technology adapts to changing HPC workloads, Robert Roe looks at the technologies that could help to enhance performance and accessibility of
storage in HPC

Feature

By using simulation software, road bike manufacturers can deliver higher performance products in less time and at a lower cost than previously achievable, as Keely Portway discovers