Tachyum Prodigy moves closer to volume production

The company has been making steady progress in its march toward Prodigy’s product release next year.

Tachyum further confirmed in verification that Prodigy has correctly executed instructions directly from DDR5 memory through coherent mesh with the Prodigy core producing correct results.

The company also confirmed that this latest Prodigy post-layout netlist maintains clock speed targets with no die size growth from its previous netlist layout milestone.

With Prodigy’s first package pin-out done, cache miss handling over coherent interconnect has been verified, as have the majority of instructions.

Tachyum has successfully compiled the design to its FPGA emulation of Prodigy and has ensured that compiled processor tiles fit into the FPGA emulation system.

Full chip FPGA emulation will be released to layout and manufacturing within the next few weeks. These achievements closely follow Tachyum’s previous milestones in performance testing and hardware connectivity, and software compatibility, and they continue to demonstrate that Prodigy is on its way to market in 2021.

“We continue to successfully meet every key metric of our aggressive timeline for producing Prodigy Universal Processor chips for mass deployment in data centre, AI and HPC workload environments,” said Dr. Radoslav Danilak (pictured), Tachyum founder and CEO. “By nearing 100 percent completion of the silicon design of our product, we are ensuring that organisations will finally have the performance, power efficiency and cost advantages they need to solve the most challenging issues facing them years earlier than previously expected.”

Tachyum's Prodigy can run HPC applications, convolutional neural net AI, explainable AI, general AI, bio AI and spiking neural networks, as well as normal data centre workloads on a single homogeneous processor platform, with a simple and familiar programming model.

Using CPU, GPU, TPU and other accelerators in lieu of Prodigy for these different types of workloads is grossly inefficient.

A heterogeneous processing fabric, with unique hardware dedicated to each type of workload (e.g. data centre, AI, HPC), results in a significant underutilisation of valuable hardware resources, and creates a more challenging programming environment.

Prodigy’s ability to seamlessly switch among these various workloads can change the competitive landscape and the economics of data centres, and Big-AI.

Prodigy significantly improves computational performance, energy consumption, hardware (server) utilisation and space requirements compared to existing processors provisioned in hyperscale data centres today. Prodigy will also allow Edge developers for IoT to exploit its low power / high performance, along with its simple programming model to deliver AI to the edge.

Since Prodigy is the world’s only processor that can switch between data center, AI and HPC workloads, unused servers can be used as CAPEX-free AI or HPC cloud, because the servers have already been amortised.