Hybrid Emulation Takes Center Stage


From mobile to networking to AI applications, system complexity shows no sign of slowing. These designs, which may contain multiple billion gates, must be validated, verified and tested, and it’s no longer possible to just throw the whole thing in a hardware emulator. For some time, emulation, FPGA-based prototyping, and virtual environments such as simulators have given design and verific... » read more

Challenges Grow For 5G Packages And Modules


The shift to 5G wireless networks is driving a need for new IC packages and modules in smartphones and other systems, but this move is turning out to be harder than it looks. For one thing, the IC packages and RF modules for 5G phones are more complex and expensive than today's devices, and that gap will grow significantly in the second phase of 5G. In addition, 5G devices will require an as... » read more

Will In-Memory Processing Work?


The cost associated with moving data in and out of memory is becoming prohibitive, both in terms of performance and power, and it is being made worse by the data locality in algorithms, which limits the effectiveness of cache. The result is the first serious assault on the von Neumann architecture, which for a computer was simple, scalable and modular. It separated the notion of a computatio... » read more

Differential Energy Analysis To Optimize Mobile GPU Power


Operating power has become one of the most important metrics for modern electronic devices. Qualcomm Technologies, a world-class mobile solution provider, significantly reduced power consumption in an already challenging market by performing power analysis at RTL using ANSYS PowerArtist. Qualcomm Technologies was able to reduce dynamic power by 10 percent through this approach. To read more,... » read more

Edge Complexity To Grow For 5G


Edge computing is becoming as critical to the success of 5G as millimeter-wave technology will be to the success of the edge. In fact, it increasingly looks as if neither will succeed without the other. 5G networks won’t be able to meet 3GPP’s 4-millisecond-latency rule without some layer to deliver the data, run the applications and broker the complexities of multi-tier Internet apps ac... » read more

5nm Vs. 3nm


Foundry vendors are readying the next wave of advanced processes, but their customers will face a myriad of confusing options—including whether to develop chips at 5nm, wait until 3nm, or opt for something in between. The path to 5nm is well-defined compared with 3nm. After that, the landscape becomes more convoluted because foundries are adding half-node processes to the mix, such as 6nm ... » read more

Falling Chip Forecasts


It’s time to take a pulse of the semiconductor market amid the memory downturn and trade frictions with China. For some time, the DRAM and NAND markets have been hit hard with falling prices and oversupply. Then, the Trump administration last year slapped tariffs on Chinese goods. China retaliated. And the trade war rages on between the U.S. and China. More recently, the U.S. Department... » read more

Hacking SoC IP Under Pressure


Hack@DAC certainly shows that some teams can find bugs faster than others. The hackfest, now in its third year, is a bug-finding contest for teams of university students joined by a smattering of industry members whose task is to find a bugs implanted in SoC IP.  The teams follow the practices of real-world security teams. “[The teams'] objective is to identify the security vulnerabilitie... » read more

Manufacturing Bits: June 10


Predicting warpage in packages At the recent IEEE Electronic Components and Technology Conference (ECTC) in Las Vegas, there were several papers on ways to predict variation and warpage in IC packages. Advanced packages are prone to unwanted warpage during the process flow. The warpage challenges escalate as the packages become thinner. Warpage in turn can impact yields in IC packages. ... » 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

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