Squirrels Research Labs Reveals Intel® FPGAs in Power-Efficient Next Generation Ethereum Mining Accelerators

NORTH CANTON, Ohio, Feb. 19, 2020 (GLOBE NEWSWIRE) — Squirrels Research Labs (SQRL), a world-leader in blockchain technology, today announced a flagship product in the successful JungleCat line of high-performance blockchain accelerators. With the introduction of two new modules starting at $1349, including 16GB of HBM2 in the highest capacity Intel® Stratix® 10 MX FPGAs, SQRL extends its market leadership in FPGA cryptocurrency mining solutions and customer value.

“We are incredibly excited to launch this product based around Intel’s FPGA technology,” SQRL president David Stanfill said. “The added capacity of 16GB HBM2 memory coupled with our industry leading 300W-per-chip design gives our customers unique and unparalleled access to mine even more cryptocurrencies.”

The new JungleCat modules can be used to mine top-tier cryptocurrencies using algorithms like Ethash (Ethereum), Equihash, and Cuckoo Cycle with an outstanding return, in part due to industry leading power efficiency. They also offer tremendous advantages in other data center compute workloads, including video processing, database acceleration and machine learning.

Intel Corporation (NASDAQ: INTC) is an industry pioneer in silicon across multiple verticals, and their collaboration as a supplier puts decades of experience and expertise behind the SQRL team.

“We have been working closely with Intel to optimize our product offerings for our customers’ needs,” Stanfill said. “We’re incredibly proud of the results so far, and we’re excited for the future.”

High capacity 16GB HBM allows the new JungleCat products to keep critical data closer to computational resources, reducing power and ultimately providing superior performance, even for algorithms that utilize significantly smaller amounts of memory.

“This is game changing,” Stanfill continued. “We’ve built products around HBM2 before, but with Intel’s help and the unique advantage of their…

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