NeuroBlade announced the opening of its North
American headquarters in Silicon Valley, with Co-Founder and CTO Eliad Hillel
relocating to California to drive the company's growth in the US.
The total volume
of data generated and consumed globally is expected to reach
more than 180 zettabytes by 2025. But while the database layer, consisting of
data warehouses, data lakes, and data lake houses, has evolved, the
infrastructure isn't keeping up with this data growth rate. Infrastructure has
been designed with much smaller analytics sizes in mind.
It's
increasingly complex, expensive, and time-consuming for organizations to
analyze this data. As a result, business and technology leaders cannot rely on
price performance when querying and analyzing hundreds of terabytes of data.
This creates an analysis gap where less than two-thirds of the data is
analyzed.
"The
reality is that the infrastructure for analytics has not kept up with the pace
of data creation and the need to analyze large data sets that go into the
hundreds of terabytes. The software layer has enjoyed immense innovation over
the years. Yet, little has been done to recreate such creativity within the
hardware layer," said Eliad Hillel, CTO and co-founder of NeuroBlade. "If you
look across the industry today, you'll see emerging solutions that aim to bring
compute closer to processing, but no one is addressing it systems-wide,
end-to-end, across compute, memory, storage and network. At our core,
NeuroBlade is a systems company and that's the approach we take: to accelerate
analytics on top of what the software can do, by a factor of 10x or greater, in
a transparent way to the end user. This is how we define the next era of hyper
compute for analytics that will allow data to be used for insights that advance
business success."
The
emergence of hyper compute for analytics as a category will result in solutions
that bridge the analysis gap and break down the technical boundaries that limit
real-time analytics performance. Hyper compute can fundamentally change the way
data is analyzed at scale to accomplish critical insights across any industry
vertical. The world is now entering a paradigm shift where it's less about the
amount of data you can store and more about the amount of data you can analyze
while delivering a realistic price performance.
To help
address this problem, NeuroBlade is building the industry's first open Hardware
Enhanced Query System (HEQS) of software and hardware. The HEQS is designed
end-to-end from analytical engine to silicon for dramatically faster
performance and ushers in the hyper compute for analytics category. NeuroBlade
HEQS changes how large data volume workloads are forever processed.
This is
done through a new class of processors explicitly designed for querying, with
better performance than organizations currently get with the traditional
CPU/GPU approach, as performance optimization and analytics acceleration in the
query layer is a known challenge. Existing system architectures show that the
constant shuffling of data between storage, memory, and central processing is
the primary cause of poor application performance and slow response times.
NeuroBlade recognized that current software-only approaches and architectures
couldn't scale to meet future data analytics needs, which led it to build the
computational architecture that eliminates the data movement requirements and
massively speeds up data analytics performance.
At the end
of 2021, NeuroBlade secured $83 million in Series B funding, bringing its total
investment capital to over $100 million. It has completed seven patents in the
US, with another 30 pending. Additionally, key members of NeuroBlade's
executive team will attend this year's Flash Memory Summit from
August 2 to 4 at the Santa Clara Convention Centre.