NeuroBlade is on a mission to empower the next wave of digital transformation by developing the new standard for analytics acceleration for large data.
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.
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