Energy Usage in Layers Of Computing (SLAC)


A technical paper titled “Energy Estimates Across Layers of Computing: From Devices to Large-Scale Applications in Machine Learning for Natural Language Processing, Scientific Computing, and Cryptocurrency Mining” was published by researchers at SLAC National Laboratory and Stanford University. Abstract: "Estimates of energy usage in layers of computing from devices to algorithms have bee... » read more

Energy of Computing As A Key Design Aspect (SLAC/Stanford, MIT)


A technical paper titled "Trends in Energy Estimates for Computing in AI/Machine Learning Accelerators, Supercomputers, and Compute-Intensive Applications" was published by researchers at SLAC/Stanford University and MIT. Abstract: "We examine the computational energy requirements of different systems driven by the geometrical scaling law, and increasing use of Artificial Intelligence or Ma... » read more

Holistic Die-to-Die Interface Design Methodology for 2.5-D Multichip-Module Systems


Abstract: "More than Moore technologies can be supported by system-level diversification enabled by chiplet-based integrated systems within multichip modules (MCMs) and silicon interposer-based 2.5-D systems. The division of large system-on-chip dies into smaller chiplets with different technology nodes specific to the chiplet application requirement enables the performance enhancement at the ... » read more

Lessons Learned In 4G LTE


By Ann Steffora Mutschler While 4G LTE has moved into the mainstream, there are lessons to be learned about these very complex modems, especially from the perspective of balancing power and performance. The road to mainstream wasn’t exactly smooth sailing. “4G LTE initially got a bad rap for battery life, for power consumption,” said Pete Hardee, low-power design solution marketin... » read more