Linley Spring Processor Conference 2021

April 19 - 23, 2021
Proceedings Available

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Agenda for Day Four: Thursday April 22, 2021
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8:30am-10:30amSession 6: Edge-AI Software

In edge applications, customers need to carefully balance the accuracy, performance, and power dissipation of their AI implementations. Software tools are critical to enabling these tradeoffs while taking full advantage of hardware optimizations. This session, led by The Linley Group principal analyst Bob Wheeler, will discuss how vendors are addressing these software challenges to advance AI at the edge.

Open-Source Optimization Tools for Accelerated AI Inference
Anton Kachatkou, Principal Software Engineer, Arm

Arm NPUs deliver high throughput and efficiency in AI applications on the edge. They provide significant advantage in power, performance, and area over conventional CPUs and GPUs for INT8 inferences out-of-the-box. However, further performance improvements can be unlocked by fine-tuning neural network models to take advantage of the underlying hardware architecture. This presentation will describe the recent developments in open-source machine learning tools that enable such optimizations and explore how various techniques can be combined to achieve the optimal balance between model accuracy and inference performance.

Why Software Is Critical for AI Inference Accelerators
Jeremy Roberson, Technical Director and AI Inference Software Architect, Flex Logix

In this presentation we will discuss the importance of software in maximizing the throughput, accuracy, and power of an AI inference accelerator. We examine how codeveloping software with hardware allows for architecture tradeoffs that maximize throughput/power for customer models. The software compiler must seamlessly translate data into meaningful results without knowledge of the hardware inner workings. Finally, with the continued evolution of CNN models, software adaptability will continue to drive throughput/power/cost improvements for broader adoption of AI functionality.

Accelerating Deep Neural Networks on the Mythic AMP
Ty Garibay, Vice President of Engineering, Mythic

In order to accelerate the execution of a neural network using an AI processor, a customer must first be able to get their neural network up and running. The software part of the solution is a critical, and often under-estimated, factor in the semiconductor world. This presentation will focus on the Mythic Optimization Suite and Graph Compiler, the tool flow developed by Mythic to bring up neural networks on the innovative Mythic Analog Matrix Processor (AMP) architecture, as well as the unique features and capabilities of the Mythic AMP itself.

Converting CNNs to More Efficient Event-Based AI
Anil Mankar, Cofounder, Chief Development Officer, BrainChip

The demand for ultra-low power and incremental learning is key to the future of AI.  Advanced neuromorphic computing is delivering a pathway to new technologies that are driving the ecosystem. Solving problems in machine learning such as privacy, latency, and power, neuromorphic computing is challenging the current way of AI thinking. This presentation addresses the ease of converting CNNs to the event domain by processing in the MetaTF neuromorphic environment from BrainChip, enabling designers to achieve efficient and effective AI solutions.

There will be Q&A and a panel discussion featuring above speakers.

10:30am-10:40amBreak Sponsored by GlobalFoundries
10:40am-11:40amSession 7: Signal Processing

The real world is analog, teeming with natural and man-made waveforms that span from subsonic to millimeter-wave frequencies. Sensing, receiving and transmitting such signals typically requires specialized process technologies, whereas analyzing them demands efficient digital-signal processors. This session, moderated by The Linley Group senior analyst Mike Demler, examines technologies that enable two of the fastest growing signal-processing applications: in advanced automotive systems and wireless audio.

Enabling Silicon Technologies to Address Automotive Radar Trends and Requirements
Dr. Farzad Inanlou, CTO Radar and mmWave, AIM Business Unit, GlobalFoundries

Advanced safety features for ADAS and autonomous driving capabilities are two automotive megatrends. Radar is a key component to implementing such systems. This talk will review the attributes of key silicon technologies for mmWave radar applications. Specific design examples will be given that highlight the performance and integration capabilities of the technologies that meet the stringent requirements of automotive OEMs.

DSP-Enabled Bluetooth and Audio IP Platform for TWS Earbuds
Franz Dugand, Sales and Marketing Director, Wireless IoT BU, CEVA

Wireless audio SoC design requires rare multidisciplinary technology expertise. CEVA addresses this need by offering a solution that dramatically lowers the high entry barriers to the True Wireless Stereo (TWS) audio market. This talk will present Bluebud, a turnkey IP platform based on the RivieraWaves Bluetooth 5.2 IP, system peripherals, and a single CEVA-BX1 DSP core running a complete software framework comprising a Bluetooth stack along with an advanced stereo synchronization mechanism, audio codecs, and a selection of voice and motion processing software add-ons.

For this session, each talk will have 10 minutes of Q&A immediately following.

11:40am-12:40pmBreakout sessions with today's speakers


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