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Arm’s Project Trillium Starts to Bloom

June 12, 2018

Author: Mike Demler

Arm has disclosed the first details (but not the name) of its forthcoming machine-learning processor core, which adds a deep-learning accelerator (DLA) to the Project Trillium platform. Project Trillium includes hardware and software components that enable machine-learning (ML) tasks to run on Cortex CPUs, Mali GPUs, and the new ML core (MLC); they also allow integration with third-party accelerators.

The MLC is a scalable neural-network inference engine. Arm’s design accelerates convolutions and matrix multiplication, which typically comprise 90% of a CNN’s operations. It uses 8-bit quantization and lacks support for other data formats, but INT8 is popular for inference engines. It also includes a programmable layer engine (PLE) that runs all non-convolution-layer operations in addition to providing a mechanism for running new layer types and network graphs.

The company plans to offer MLC configurations for automobiles, data centers, and IoT clients, but its first release targets mobile application processors. It tuned the design for 16nm and 7nm technologies, which it will enable with physically optimized (POP) hard-core versions. In 7nm technology, the MLC delivers up to 4.6 trillion operations per second (TOPS), and it consumes 1.5W at that peak rate. The POP intellectual property (IP) reduces the compute-engine area compared with the synthesizable-RTL version, and it reduces power by 10–20%. Several processor vendors are evaluating the MLC, and Arm plans to release the RTL and POP IP in 3Q18.

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