Optimizing Power For Learning At The Edge


Learning on the edge is seen as one of the Holy Grails of machine learning, but today even the cloud is struggling to get computation done using reasonable amounts of power. Power is the great enabler—or limiter—of the technology, and the industry is beginning to respond. "Power is like an inverse pyramid problem," says Johannes Stahl, senior director of product marketing at Synopsys. "T... » read more

Target: 50% Reduction In Memory Power


Memory consumes about 50% or more of the area and about 50% of the power of an SoC, and those percentages are likely to increase. The problem is that static random access memory (SRAM) has not scaled in accordance with Moore's Law, and that will not change. In addition, with many devices not chasing the latest node and with power becoming an increasing concern, the industry must find ways to... » read more

Using Analog For AI


If the only tool you have is a hammer, everything looks like a nail. But development of artificial intelligence (AI) applications and the compute platforms for them may be overlooking an alternative technology—analog. The semiconductor industry has a firm understanding of digital electronics and has been very successful making it scale. It is predictable, has good yield, and while every de... » read more

Alchip Minimizes Dynamic Power For High-Performance Computing ASICs


Alchip, a fabless ASIC provider, focuses on high-performance computing ASICs. They decided to undertake a new project where they would employ the PowerPro RTL Low-Power Platform to reduce dynamic power consumption within their unique fishbone clock tree methodology. Could they achieve better power results using PowerPro and could they integrate the tool within their team and the existing design... » read more