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Making Sense Of New Edge-Inference Architectures


New edge-inference machine-learning architectures have been arriving at an astounding rate over the last year. Making sense of them all is a challenge. To begin with, not all ML architectures are alike. One of the complicating factors in understanding the different machine-learning architectures is the nomenclature used to describe them. You’ll see terms like “sea-of-MACs,” “systolic... » read more

Mythic Case Study


Mythic, the provider of a unique AI compute platform, was designing an innovative intelligence processing unit (IPU) and found themselves in need of a small, power-efficient, yet programmable core to take care of specific supporting functions. As no off-the-shelf core would exactly match the needs and customization proved challenging, Mythic eventually opted for a complete solution by Codasip. ... » read more

Week In Review: Design, Low Power


AI Mythic debuted its Analog Matrix Processor for edge AI applications such as smart home, AR/VR, drones, video surveillance, smart city, and industrial. The M1108 AMP combines 108 tiles made up of an array of flash cells and ADCs, a 32-bit RISC-V nano-processor, a SIMD vector engine, SRAM, and a high-throughput Network-on-Chip router. It uses 40nm technology and the company says typical power... » read more

Week In Review: Auto, Security, Pervasive Computing


Pervasive computing — Data centers, cloud, 5G, edge In a move to improve data collection for IC manufacturing, PDF Solutions entered a definitive agreement to acquire Cimetrix Incorporated. Cimetrix makes connectivity products for smart manufacturing, which PDF Solutions will use in its Exensio product to facilitate moving IC manufacturing data from the factory floor to cloud-based analytics... » read more

Creating Better Models For Software And Hardware Verification


Semiconductor Engineering sat down to discuss what's ahead for verification with Daniel Schostak, Arm fellow and verification architect; Ty Garibay, vice president of hardware engineering at Mythic; Balachandran Rajendran, CTO at Dell EMC; Saad Godil, director of applied deep learning research at Nvidia; Nasr Ullah, senior director of performance architecture at SiFive. What follows are excerpt... » read more

Simplifying And Speeding Up Verification


Semiconductor Engineering sat down to discuss what's ahead for verification with Daniel Schostak, Arm fellow and verification architect; Ty Garibay, vice president of hardware engineering at Mythic; Balachandran Rajendran, CTO at Dell EMC; Saad Godil, director of applied deep learning research at Nvidia; Nasr Ullah, senior director of performance architecture at SiFive. What follows are excerpt... » read more

What Will The Next-Gen Verification Flow Look Like?


Semiconductor Engineering sat down to discuss what's ahead for verification with Daniel Schostak, Arm fellow and verification architect; Ty Garibay, vice president of hardware engineering at Mythic; Balachandran Rajendran, CTO at Dell EMC; Saad Godil, director of applied deep learning research at Nvidia; and Nasr Ullah, senior director of performance architecture at SiFive. What follows are exc... » read more

Inevitable Bugs


Are bug escapes inevitable? That was the fundamental question that Oski Technology recently put to a group of industry experts. The participants are primarily simulation experts who, in many cases, help direct the verification directions for some of the largest systems companies. In order to promote free discussion, all comments have been anonymized, distilling the primary thoughts of the parti... » read more

Memory Issues For AI Edge Chips


Several companies are developing or ramping up AI chips for systems on the network edge, but vendors face a variety of challenges around process nodes and memory choices that can vary greatly from one application to the next. The network edge involves a class of products ranging from cars and drones to security cameras, smart speakers and even enterprise servers. All of these applications in... » read more

Week In Review: Design, Low Power


Processors Arm rolled out a micro neural processing unit that, when combined with its newest microcontroller, can increase machine learning performance by up to 480 times. The company is aiming the MCU and co-processor across a wide swath of applications. Worth noting is that Arm calls its Cortex-M55 an AI-capable processor, rather than a microcontroller, as the lines between the various proce... » read more

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