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Year in Review: IP Suppliers Push AI Accelerators

January 8, 2019

Author: Mike Demler

In 2018, to meet increasing demand for on-device AI such as face and voice recognition, intellectual-property (IP) vendors added neural-network functions to all types of processor IP, from CPUs, DSPs, and GPUs to dedicated deep-learning accelerators (DLAs). Several vendors rolled out DLAs with large multiply-accumulate units, which boost neural-network performance, and some introduced multicore configurations. These licensable cores enable AI to expand from data centers to the edge, serving in IoT sensors, smart speakers, smartphones, and many other client devices.

In traditional CPU IP, the open-source movement that RISC-V ISA proponents began shows no signs of slowing. Designers can choose from a growing list of vendors offering verified cores. First-generation RISC-V CPUs targeted embedded microcontrollers, but new generations compete with some of Arm’s Cortex-A CPUs. The open-source business model is catching on with other companies as well. Wave Computing announced plans to open the MIPS Release-6 ISA, and Nvidia opened the DLA in the Xavier autonomous-driving processor.

Although RISC-V is an alternative to some of Arm’s low-performance tiers, Cortex-A CPUs are moving into market segments that were previously the exclusive domain of x86. The company’s new Cortex-A76 powers Windows-on-Arm PCs, and Amazon announced plans to use custom Arm-v8-based processors in its cloud-computing service.

In 2019, we expect most DLA vendors will include weight compression and variable precision as standard features, shifting their emphasis to greater area and power efficiency. In the coming year, Arm will embark on its new strategy, adding to its traditional Cortex portfolio but also launching two other product lines: “automotive enhanced” cores and the Neoverse family, which is optimized for data centers and infrastructure.

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