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Software-defined processor startup selects UltraSoC IP

Software-defined processor startup selects UltraSoC IP

Technology News |
By Peter Clarke



SimpleMachines’ approach to computing in the datacenter is in essence that hardware should be malleable and conform to software requirements. The implication is that there is a benefit to simplifying and slowing the hardware down to allow for rapid reconfiguration.

The Composable Computing Platform is somewhat akin to a reconfigurable FPGA. The software API, compiler and hardware implementation analyse a program’s properties in terms of shape, size and data requirements. The software stack transforms the layout of the processor’s storage and execution units on-the-fly to match the data and computation patterns.

The technology has been applied to convolutional neural networks, long short-term memory recurrent neural networks, transformers, and regression trees.

UltraSoC’s embedded analytics are being designed into SiliconMachine’s processors allowing monitoring of internal bus transactions, processor execution and other system-wide behaviors within the device.

This allows performance of a custom chip built for that application, in a multitude of circumstances. Reconfiguration is described as taking milliseconds, which does represent thousands of clock cycles.

The software around the reconfigurable processor identifies four fundamental behaviors: data-fetch, synchronization, computation, and control. Once identified, the chip directly implements the four behaviors at the basic level of a tile. The processor integrates 128 such tiles interconnected with an on-chip network. A dynamic runtime engine provides an abstraction of thousands of such tiles and in effect, performs the layout and synthesis tasks that an ASIC designer would have taken months to complete for a single custom chip.

The compiler has been designed to integrate into the backends of the popular machine learning development environments TensorFlow, ONNX, and PyTorch.

The company was founded by Karu Sankaralingam, an associate professor of computer science at the University of Wisconsin–Madison, in 2016 and raised $2.9 million in seed funding in 2017. In 2018 Baidu Ventures and IMO Ventures contributed to a $16.7 millon Series A round of equity funding.

Simulation tools, emulation tools, an SDK, and a limited number of FPGA trial cards are available. First silicon samples of the Composable Compute Platform will be available during the summer of 2020.

The first product will be the ‘Mozart’ PCIe card that incorporates the processor, which SimpleMachines claims will provide between 5x and 100x speed up in artificial intelligence applications.

“SimpleMachines’ Composable Computing concept is a genuine game-changer for emerging data-driven applications,” said Gajinder Panesar, CTO of UltraSoC, in a statement. “The problems they’re addressing are traditionally seen as needing a hard-wired solution – and often that means costly and time-consuming ASIC development. Clever new hardware architectures also often overlook how the software developer will use, debug, or understand that architecture. We’re delighted to have the opportunity to work with SMI and to support the team as they deliver solutions to arguably some of the world’s trickiest computing problems.”

SimpleMachines CEO, Karu Sankaralingam, added: “UltraSoC is the only company that can provide intimate visibility of the operation of our chips – which is vital as we implement our architecture. The embedded insights UltraSoC’s technology delivers will be essential for customers as they develop solutions, and will increasingly be a must-have even when devices are deployed in the field. Having UltraSoC in our chips addresses the need for a system-level view of performance that makes software development and hardware integration much more efficient.”

Related links and articles:

www.simplemachinesinc.com

www.ultrasoc.com

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