Future-proofing AI Models


Experts At The Table: Making sure AI accelerators can be updated for future requirements is becoming essential due to the rapid introduction of new models. Semiconductor Engineering sat down to discuss the challenges of future-proofing these designs with Marc Meunier, director of ecosystem development at Arm; Jason Lawley, director of product marketing for AI IP at Cadence; Paul Karazuba, vic... » read more

AI Accelerators Moving Out From Data Centers


Experts At The Table: The explosion in AI data is driving chipmakers to look beyond a single planar SoC. Semiconductor Engineering sat down to discuss the need for more computing and the expanding role of chiplets with Marc Meunier, director of ecosystem development at Arm; Jason Lawley, director of product marketing for AI IP at Cadence; Paul Karazuba, vice president of marketing at Expedera; ... » read more

Challenges In Managing Chiplet Resources


Managing chiplet resources is emerging as a significant and multi-faceted challenge as chiplets expand beyond the proprietary designs of large chipmakers and interact with other elements in a package or system. Poor resource management in chiplets adds an entirely new dimension to the usual power, performance, and area tradeoffs. It can lead to performance bottlenecks, because as chiplets co... » read more

Scalability of Nanosheet Oxide FETs for Monolithic 3-D Integration


A new technical paper titled "High-Field Transport and Statistical Variability of Nanosheet Oxide Semiconductor FETs With Channel Length Scaling" was published by researchers at The University of Tokyo and Nara Institute of Science and Technology. Abstract "We have investigated the scaling potential of nanosheet oxide semiconductor FETs (NS OS FETs) for monolithic 3-D (M3D) integration in t... » read more

GPU Microarchitecture Integrating Dedicated Matrix Units At The Cluster Level (UC Berkeley)


A new technical paper titled "Virgo: Cluster-level Matrix Unit Integration in GPUs for Scalability and Energy Efficiency" was published by UC Berkeley. Abstract "Modern GPUs incorporate specialized matrix units such as Tensor Cores to accelerate GEMM operations central to deep learning workloads. However, existing matrix unit designs are tightly coupled to the SIMT core, limiting the size a... » read more

SARA: Scaling a Reconfigurable Dataflow Accelerator


Yaqi Zhang, Nathan Zhang, Tian Zhao, Matt Vilim, Muhammad Shahbaz, Kunle Olukotun (Stanford) Abstract—"The need for speed in modern data-intensive workloads and the rise of “dark silicon” in the semiconductor industry are pushing for larger, faster, and more energy and areaefficient architectures, such as Reconfigurable Dataflow Accelerators (RDAs). Nevertheless, challenges remain in d... » read more

Yikes! Why Is My SystemVerilog Testbench So Slooooow?


It turns out that [gettech id="31023" comment="SystemVerilog"] != [gettech id="31017" comment="verilog"]. OK, we all figured that out a few years ago as we started to build verification environments using [gettech id="31026" comment="IEEE 1800"] SystemVerilog. While it did add design features like new ways to interface code, it also had verification features like classes, dynamic data types, ... » read more