Regulations Trail Autonomous Vehicles


Fragmented regulations and unrealistic expectations may be the biggest hurdles for chipmakers selling into the market for self-driving cars during the next few years. Carmakers and the semiconductor industry have made tremendous progress building real-time vision systems and artificial intelligence into relatively traditional automobiles during the past decade or so. But federal and state re... » read more

Hardware Acceleration With eFPGAs


If integrating an embedded FPGA (eFPGA) into your ASIC or SoC design strikes you as odd, it shouldn’t. ICs have been absorbing almost every component on a circuit board for decades, starting with transistors, resistors, and capacitors –– then progressing to gates, ALUs, microprocessors, and memories. FPGAs are simply one more useful component in the tool box, available for decades and ... » read more

FPGAs Becoming More SoC-Like


FPGAs are blinged-out rockstars compared to their former selves. No longer just a collection of look-up tables (LUTs) and registers, FPGAs have moved well beyond into now being architectures for system exploration and vehicles for proving a design architecture for future ASICs. This family of devices now includes everything from basic programmable logic all the way up to complex SoC devices.... » read more

New Deep Learning Processors, Embedded FPGA Technologies, SoC Design Solutions


Some of the most valuable events at DAC are the IP Track sessions, which give small and midsize companies a chance to share innovations that might not get much attention elsewhere. The use of IP in SoCs has exploded in recent years. In a panel at DAC 2017, an industry expert noted that the IP market clearly was growing even faster than EDA itself, due to the fact that more and more chip mak... » read more

Challenges At The Edge


By Kevin Fogarty and Ed Sperling Edge computing is inching toward the mainstream as the tech industry begins grappling with the fact that far too much data will be generated by sensors to send everything back to the cloud for processing. The initial idea behind the IoT/IIoT, as well as other connected devices, was that simple sensors would relay raw data to the cloud for processing throug... » read more

The Week In Review: Design


M&A Alibaba acquired C-Sky Microsystems, which focuses on 32-bit embedded CPU IP cores in both low power and high performance varieties, as well as SoC and MCU platforms. Founded in 2001, the Hangzhou, China-based C-Sky previously received investment from Alibaba, and the two companies collaborated on a hardware and software platform for IoT and cloud integration. The deal comes on the hee... » read more

New Market Drivers


Semiconductor Engineering sat down to discuss changing market dynamics with Steve Mensor, vice president of marketing for [getentity id="22926" e_name="Achronix"]; Apurva Kalia, vice president of R&D in the System and Verification group of [getentity id="22032" e_name="Cadence"]; Mohammed Kassem, CTO for [getentity id="22910" comment="efabless"]; Matthew Ballance, product engineer and techn... » read more

Designing 5G Chips


5G is the wireless technology of the future, and it’s coming fast. The technology boasts very high-speed data transfer rates, much lower latency than 4G LTE, and the ability to handle significantly higher densities of devices per cell site. In short, it is the best technology for the massive amount of data that will be generated by sensors in cars, IoT devices, and a growing list of next-g... » read more

The Week In Review: Design


Tools & IP Cadence unveiled its latest DSP for embedded vision and AI, Tensilica Vision Q6 DSP. The DSP is built on a 13-stage processor pipeline and new system architecture designed for use with large local memories, and achieves 1.5GHz peak frequency and 1GHz typical frequency at 16nm. Compared to its predecessor, it offers 1.5X greater vision and AI performance than its predecessor and ... » read more

High-Performance Memory Challenges


Designing memories for high-performance applications is becoming far more complex at 7/5nm. There are more factors to consider, more bottlenecks to contend with, and more tradeoffs required to solve them. One of the biggest challenges is the sheer volume of data that needs to be processed for AI, machine learning or deep learning, or even in classic data center server racks. “The design... » read more

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