tag: AI

The Precision Knob
By Ed Sperling - 18 Apr, 2019 - Comments: 0

Precision used to be a goal, but increasingly it is being used as a tool. This is true for processing and algorithms, where less precision can greatly improve both performance and battery life. And it is true in manufacturing, where more precision can help minimize the growing impact of variation. Moreover, being able to dial precision up or down can help engineers see the impact on a system... » read more

Blog Review: April 17
By Jesse Allen - 17 Apr, 2019 - Comments: 0

In a video, Mentor's Colin Walls digs into power management in embedded software with a particular look at the Power Pyramid model. Synopsys' Taylor Armerding checks out the state of application security at this year's RSA and finds that while organizations are paying attention to security through training and dedicated teams, roadblocks still remain. Cadence's Paul McLellan considers how... » read more

Power/Performance Bits: April 16
By Jesse Allen - 16 Apr, 2019 - Comments: 0

Faster CNN training Researchers at North Carolina State University developed a technique that reduces training time for deep learning networks by more than 60% without sacrificing accuracy. Convolutional neural networks (CNN) divide images into blocks, which are then run through a series of computational filters. In training, this needs to be repeated for the thousands to millions of images... » read more

Multi-Layer Processing Boosts Inference Throughput/Watt
By Geoff Tate - 15 Apr, 2019 - Comments: 0

The focus in discussion of inference throughput is often on the computations required. For example, YOLOv3, a power real time object detection and recognition model, requires 227 BILLION MACs (multiply-accumulates) to process a single 2 Mega Pixel image! This is with the Winograd Transformation; it’s more than 300 Billion without it. And there is a lot of discussion of the large size ... » read more

Week in Review: IoT, Security, Auto
By Jeff Dorsch - 12 Apr, 2019 - Comments: 0

Internet of Things Smart-building technology is a factor in marketing new facilities to prospective tenants. The new Cambridge Crossing development in Cambridge, Mass., aspires to attract tech-oriented tenants much like nearby Kendall Square, this analysis notes. Philips has agreed to lease seven floors in Cambridge Crossing’s first office building, making that location its North American he... » read more

Week In Review: Design, Low Power
By Jesse Allen - 12 Apr, 2019 - Comments: 0

IP Flex Logix debuted its new InferX X1 edge inference co-processor, which incorporates the interconnect technology from its eFPGAs and its inference-optimized nnMAX clusters. The chip focuses on high throughput in edge applications with a single DRAM and is optimized for small batch sizes in edge applications where there is typically only one camera/sensor. InferX X1 will be available as chip... » read more

More Memory And Processor Tradeoffs
By Ed Sperling - 11 Apr, 2019 - Comments: 0

Creating a new chip architecture is becoming an increasingly complex series of tradeoffs about memories and processing elements, but the benefits are not always obvious when those tradeoffs are being made. This used to be a fairly straightforward exercise when there was one processor, on-chip SRAM and off-chip DRAM. Fast forward to 7/5nm, where chips are being developed for AI, mobile ph... » read more

GDDR6 And HBM2: Signal Integrity Challenges For AI
By Frank Ferro - 11 Apr, 2019 - Comments: 0

In a nutshell, Artificial Intelligence (AI) and its growing list of applications demand a considerably large amount of bandwidth to push bits in and out of memory at the highest speeds possible. AI has been getting a lot of industry attention, and certainly it’s not a new phenomenon because it’s been gaining even greater traction in the last year or two. This is especially true since a n... » read more

Multi-Physics At 5/3nm
By Ed Sperling - 11 Apr, 2019 - Comments: 0

Joao Geada, chief technologist at ANSYS, talks about why timing, process, voltage, and temperature no longer can be considered independently of each other at the most advanced nodes, and why it becomes more critical as designs shrink from 7nm to 5nm and eventually to 3nm. In addition, more chips are being customized, and more of those chips are part of broader systems that may involve an AI com... » read more

From AI Algorithm To Implementation
By Brian Bailey - 10 Apr, 2019 - Comments: 0

Semiconductor Engineering sat down to discuss the role that EDA has in automating artificial intelligence and machine learning with Doug Letcher, president and CEO of Metrics; Daniel Hansson, CEO of Verifyter; Harry Foster, chief scientist verification for Mentor, a Siemens Business; Larry Melling, product management director for Cadence; Manish Pandey, Synopsys fellow; and Raik Brinkmann, CEO ... » read more

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