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Tachyum Readying First Tape-out of its Prodigy SoCs

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Tachyum announced today it will cease taking orders for its Prodigy Universal Processor Field Programmable Gate Array (FPGA) emulation system boards effective immediately. The company releases the final Prodigy build for tape-out. New partners and customers who wish to work with Prodigy FPGAs for product evaluation, performance measurements, software development, debugging and compatibility testing can arrange for private testing in Tachyum's facility. As these are shared systems, they can't be used for classified or proprietary data or data subject to regulatory governance.

The Prodigy hardware emulator consists of multiple FPGA and IO boards connected by cables in a rack. A single board with four FPGAs emulates eight Prodigy processor cores (a small fraction of the final Prodigy product design, which consists of 128 cores) including vector and matrix fixed and floating-point processing units. Deploying more FPGAs will improve test cycles by orders of magnitudes to achieve target quality, a risk reduction mechanism for early adopters.




"We thank those who have worked with our prototypes, put Prodigy to the test in their environments, validated compatibility with their hardware and software systems, and provided feedback to our team," said Radoslav Danilak, founder and CEO of Tachyum. "Concluding this stage of Prodigy's development brings us closer to the finish line, closer to volume production, and closer to transforming the industry with unprecedented processing power and efficiency."

Prodigy delivers unprecedented data center performance, power, and economics, reducing CAPEX and OPEX significantly. Because of its utility for both high-performance and line-of-business applications, Prodigy-powered data center servers can seamlessly and dynamically switch between workloads, eliminating the need for expensive dedicated AI hardware and dramatically increasing server utilization. Tachyum's Prodigy integrates 128 high-performance custom-designed 64-bit compute cores, to deliver up to 4x 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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