Arm unveils Project Trillium processors for mobile machine learning

machine learning chip AI for yr brain
Image credit: Karsten Neglia / Shutterstock.com

Arm has announced Project Trillium, an IP suite that includes new highly scalable processors that it says will deliver enhanced machine learning (ML) and neural network (NN) functionality.

Arm says the current technologies are focused on the mobile market and will enable a new class of ML-equipped devices with advanced compute capabilities, including object detection.

Current ML technologies tend to focus on specific device classes or the needs of individual sectors. While the initial Project Trillium launch focuses on mobile processors, future Arm ML products will deliver the ability to move up or down the performance curve – from sensors and smart speakers, to mobile, home entertainment, and beyond, said Rene Haas, president of Arm’s IP Products Group.

“The rapid acceleration of artificial intelligence into edge devices is placing increased requirements for innovation to address compute while maintaining a power efficient footprint,” said Haas. “New devices will require the high-performance ML and AI capabilities these new processors deliver. Combined with the high degree of flexibility and scalability that our platform provides, our partners can push the boundaries of what will be possible across a broad range of devices.”

Arm’s new ML and object detection processors not only provide a massive efficiency uplift from standalone CPUs, GPUs and accelerators, but they far exceed traditional programmable logic from DSPs.

The Arm ML processor is built from the ground-up, specifically for ML. It is based on the highly scalable Arm ML architecture and achieves the highest performance and efficiency for ML applications:

  • For mobile computing, the processor delivers more than 4.6 trillion operations per second (TOPs) with a further uplift of 2x-4x in effective throughput in real-world uses through intelligent data management
  • Unmatched performance in thermal and cost-constrained environments with an efficiency of over three trillion operations per second per watt (TOPs/W). More details on the Arm ML processor are available on our website.

The Arm OD processor has been designed specifically to efficiently identify people and other objects with virtually unlimited objects per frame:

  • Real-time detection with Full HD processing at 60 frames per second
  • Up to 80x the performance of a traditional DSP, and a significant improvement in detection quality relative to previous Arm technologies.

Arm NN software, when used alongside the Arm Compute Library and CMSIS-NN, is optimized for NNs and bridges the gap between NN frameworks such as TensorFlow, Caffe, and Android NN and the full range of Arm Cortex CPUs, Arm Mali GPUs, and ML processors. Developers get the highest performance from ML applications by being able to fully-utilize underlying Arm hardware capabilities and performance, Arm says.

The new suite of Arm ML IP will be available for early preview in April of this year, with general availability in mid-2018.

Arm added that Project Trillium is not the commercial brand name for its machine learning technology – it’s a codename that will eventually be replaced by the commercial brand name.

Be the first to comment

What do you think?

This site uses Akismet to reduce spam. Learn how your comment data is processed.