Tachyum Builds Last FPGA Prototypes Batch Ahead of Tape-Out

Tachyum today announced the final build of its Prodigy FPGA emulation system in advance of chip production and general availability next year.

Tachyum today announced the final build of its Prodigy FPGA emulation system in advance of chip production and general availability next year. As part of the announcement, the company is also ending its purchase program for prototype systems that was previously offered to commercial and federal customers.

These last hardware FPGA prototype units will ensure Tachyum hits its extreme-reliability test targets of more than 10 quadrillion cycles prior to tape-out and before the first Prodigy chips hit the market. Tachyum’s software emulation system – and access to it – is expanding with additional availability of open-source software ported ahead of Prodigy’s upstreaming.

Additional modifications included in this final build include:

“Reaching this point of our development journey prior to tape-out and volume production of Prodigy processors next year is extremely gratifying,” said Dr. Radoslav Danilak, founder and CEO of Tachyum. “Our commitment to delivering the world’s smallest, fastest and greenest general-purpose chip has remained unwavering. Ensuring this happens Day One of launch has been a priority for us and we are excited to be on the precipice of this industry-altering release.”

As a Universal Processor offering industry-leading performance for all workloads, Prodigy-powered data center servers can seamlessly and dynamically switch between computational domains (such as AI/ML, HPC, and cloud) with a single homogeneous architecture. By eliminating the need for expensive dedicated AI hardware and dramatically increasing server utilization, Prodigy reduces CAPEX and OPEX significantly while delivering unprecedented data center performance, power, and economics. Prodigy integrates 192 high-performance custom-designed 64-bit compute cores, to deliver up to 4.5x the performance of the highest-performing x86 processors for cloud workloads, up to 3x that of the highest performing GPU for HPC, and 6x for AI applications.

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