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Real FAST DATA Processing with GPU

Real FAST DATA Processing with GPU Engine Potentially up to Three Orders of Magnitude Faster, While Also Reducing Power and Space Requirements by up to 90 Percent.

FASTDATA.IO RAISES $1.5 MILLION FROM NVIDIA AND OTHERS TO LAUNCH TRUE REAL-TIME STREAM PROCESSING ENGINE

SANTA MONICA, Calif., May 4, 2017 – Fastdata.io, a real-time stream processing company, today announced it has raised a total of $1.5 million from NVIDIA and other investors. The company is set to revolutionize the stream processing market by introducing the world’s fastest and most efficient stream processing software engine to meet the critical and growing need for efficient, real-time big data processing. Fastdata.io will use the financing to invest in developing the company’s product, marketing and talent acquisition.

Fastdata.io is led by CEO and founder Alen Capalik, an industry veteran who has significant expertise directing low-level kernel development for high-frequency trading financial systems and advanced cybersecurity technology. Fastdata.io has developed high performance computing (HPC) software, called FDIO Engine™, which exploits the massively parallel processing capability of NVIDIA GPUs to provide economical real-time, inline processing of big data in motion.
By processing extremely complex algorithms against terabytes of live streaming data, the FDIO Engine will:

Accelerate three orders of magnitude faster than competing stream processing engines available on the market today, with scale up potential up to five orders of magnitude on certain workloads. This paradigm shift in speed will open exciting new possibilities for application development in industries that require real-time processing like finance, fraud, security, artificial intelligence, machine learning, virtual and augmented reality, Internet of Things and autonomous vehicles.

Reduce power requirements by more than 90% in the data center whether running in the public cloud or on private servers. This new level of efficiency will save billions of dollars in power costs while tremendously reducing carbon emissions for cloud providers.

“Our FDIO Engine is unique in the industry, built from the ground up for both speed and efficiency. It can process large amounts of streaming data while natively accelerating any existing algorithms out of the box. This was made possible by low-level programming and harnessing the sheer power of NVIDIA’s efficient GPU technology,” said Alen Capalik, CEO and founder of fastdata.io. “The FDIO Engine will exploit NVIDIA’s latest GPUs and its CUDA API to make stream processing so much more efficient that it will usher in a new era, opening endless innovative opportunities for businesses to exploit economical, real-time data processing.”  “Fastdata.io is one of the most innovative AI startups that we have seen using NVIDIA’s GPU-based platform to provide truly real-time stream processing,” said Jeff Herbst, vice president of business development at NVIDIA. “By leveraging CUDA and our most advanced GPU technology, the FDIO Engine promises to offer unmatched efficiency and power savings to drive new technologies forward.”
Fastdata.io will exhibit at the GPU Technology Conference on May 8-11, 2017, in San Jose, California and participate in the exclusive NVIDIA AI Day for Select VCs on May 10 at the conference. Come visit fastdata.io at booth #1023.

About fastdata.io
Fastdata.io is introducing the world’s fastest and most efficient stream processing software engine. Leveraging general-purpose computing on graphics processing units, fastdata.io has developed its FDIO Engine™, a high performance computing software engine, to exploit the massively parallel processing capability of NVIDIA’s GPU platform. The FDIO Engine scales stream processing potentially up to three orders of magnitude faster, while simultaneously cutting power and space requirements in the data center by more than 90%. The company was founded in 2016 by Alen Capalik. Fastdata.io is headquartered in Santa Monica, California with offices in Seattle, Washington.

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