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

Synopsys FPGA Platform: Enabling Faster Design, Verification and Debug of FPGAs


Field programmable gate arrays (FPGAs) are no longer the co-processor of full-custom chips and application-specific integrated circuits (ASICs). Today's FPGA offerings include devices as large and complex as any ASIC system-on-chip (SoC) on the market. The dramatic increase in size, complexity and functionality means that many FPGA development teams are adopting ASIC-style design, verification ... » read more

IP Security In FPGAs


Quinn Jacobson, strategic architect at Achronix, talks about security in FPGAs, including how to prevent reverse engineering of IP, how to make sure the design is authentic, and how to limit access to IP in transit and in the chip. » read more

Enabling Faster Design, Verification and Debug of FPGAs


Field programmable gate arrays (FPGAs) are no longer the co-processor of full-custom chips and application-specific integrated circuits (ASICs). Today’s FPGA offerings include devices as large and complex as any ASIC system-on-chip (SoC) on the market. The dramatic increase in size, complexity and functionality means that many FPGA development teams are adopting ASIC-style design, verificatio... » read more

Synthesizing Hardware From Software


The ability to automatically generate optimized hardware from software was one of the primary tenets of system-level design automation that was never fully achieved. The question now is whether that will ever happen, and whether it is just a matter of having the right technology or motivation to make it possible. While high-level synthesis (HLS) did come out of this work and has proven to be... » read more

Smart NiCs


Manish Sinha, strategic planning for marketing and business at Achronix, talks with Semiconductor Engineering about what’s changing in networking interface cards, how to get more performance out of these devices, and how much needs to be in hardware versus software. » read more

Power Is Limiting Machine Learning Deployments


The total amount of power consumed for machine learning tasks is staggering. Until a few years ago we did not have computers powerful enough to run many of the algorithms, but the repurposing of the GPU gave the industry the horsepower that it needed. The problem is that the GPU is not well suited to the task, and most of the power consumed is waste. While machine learning has provided many ... » read more

Inferencing Efficiency


Geoff Tate, CEO of Flex Logix, talks with Semiconductor Engineering about how to measure efficiency in inferencing chips, how to achieve the most throughput for the lowest cost, and what the benchmarks really show. » read more

Security’s Very Strange Path To Success


Security at the chip level appears to be heading toward a more promising future. The reason is simple—more people are willing to pay for security than in the past. For the most part, security is like insurance. You don't know it's working until something goes wrong, and you don't necessarily even know right away if there has been a breach. Sometimes it takes years to show up, because it ca... » read more

Disregard Safety And Security At Your Own Peril


Semiconductor Engineering sat down to discuss industry attitudes towards safety and security with Dave Kelf, chief marketing officer for Breker Verification; Jacob Wiltgen, solutions architect for functional safety at Mentor, a Siemens Business; David Landoll, solutions architect for OneSpin Solutions; Dennis Ciplickas, vice president of characterization solutions at PDF Solutions; Andrew Dauma... » read more

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