FPGA Design Tradeoffs Getting Tougher


FPGAs are getting larger, more complex, and significantly harder to verify and debug. In the past, FPGAs were considered a relatively quick and simple way to get to market before committing to the cost and time of developing an ASIC. But today, both FPGAs and eFPGAs are being used in the most demanding applications, including cloud computing, AI, machine learning, and deep learning. In some ... » read more

eFPGA Macros Deliver Higher Speeds from Less Area/Resources


We work with a lot of customers designing eFPGA into their SoCs.  Most of them have “random logic” RTL, but some customers have large numbers of complex, frequently used blocks. We have found in many cases that we can help the customer achieve higher throughput AND use less silicon area with Soft Macros. Let’s look at an example: 64x64 Multiply-Accumulate (MAC), below: If yo... » read more

Why Scaling Must Continue


The entire semiconductor industry has come to the realization that the economics of scaling logic are gone. By any metric—price per transistor, price per watt, price per unit area of silicon—the economics are no longer in the plus column. So why continue? The answer is more complicated than it first appears. This isn't just about inertia and continuing to miniaturize what was proven in t... » read more

Accelerating Endpoint Inferencing


Chipmakers are getting ready to debut inference chips for endpoint devices, even though the rest of the machine-learning ecosystem has yet to be established. Whatever infrastructure does exist today is mostly in the cloud, on edge-computing gateways, or in company-specific data centers, which most companies continue to use. For example, Tesla has its own data center. So do most major carmake... » read more

Speeding Up AI


Robert Blake, president and CEO of Achronix, sat down with Semiconductor Engineering to talk about AI, which processors work best where, and different approaches to accelerate performance. SE: How is AI affecting the FPGA business, given the constant changes in algorithms and the proliferation of AI almost everywhere? Blake: As we talk to more and more customers deploying new products and... » read more

How To Meet Power Performance And Cost for Autonomous Vehicle Systems Using Speedcore eFPGAs


In the advanced, fully autonomous, self-driving vehicles of the future, the existence of dozens and even hundreds of distributed CPUs and numerous other processing elements is assured. Peripheral sensor-fusion and other processing tasks can be served by ASICs, SoCs, or traditional FPGAs. But the introduction of embedded FPGA blocks such as Achronix's Speedcore eFPGA IP provides numerous system-... » read more

Inferencing At The Edge


Geoff Tate, CEO of Flex Logix, talks about the challenges of power and performance at the edge, why this market is so important from a business and technology standpoint, and what factors need to be balanced. » read more

CEO Outlook: It Gets Much Harder From Here


Semiconductor Engineering sat down to discuss what's changing across the semiconductor industry with Wally Rhines, CEO emeritus at Mentor, a Siemens Business; Jack Harding, president and CEO of eSilicon; John Kibarian, president and CEO of PDF Solutions; and John Chong, vice president of product and business development for Kionix. What follows are excerpts of that discussion, which was held in... » read more

How To Integrate An Embedded FPGA


Choosing to add programmable logic into an SoC with an eFPGA is just the beginning. Other choices follow involving how many lookup tables (LUTs), how much routing and what topology, how will data be transferred in and out of the fabric, does data need to be coherent with system memory, how will it be programmed and tested, and what RTL functions need to be embedded into the programmable fabric ... » read more

The Case For Embedded FPGAs Strengthens And Widens


The embedded FPGA, an IP core integrated into an ASIC or SoC, is winning converts. System architects are starting to see the benefits of eFPGAs, which offer the flexibility of programmable logic without the cost of FPGAs. Programmable logic is especially appealing for accelerating machine learning applications that need frequent updates. An eFPGA can provide some architects the cover they ne... » read more

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