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

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

Memory Options And Tradeoffs


Steven Woo, Rambus fellow and distinguished inventor, talks with Semiconductor Engineering about different memory options, why some are better than others for certain tasks, and what the tradeoffs are between the different memory types and architectures.     Related Articles/Videos Memory Tradeoffs Intensify In AI, Automotive Applications Why choosing memories and archi... » read more

Do Large Batches Always Improve Neural Network Throughput?


Common benchmarks like ResNet-50 generally have much higher throughput with large batch sizes than with batch size =1. For example, the Nvidia Tesla T4 has 4x the throughput at batch=32 than when it is processing in batch=1 mode. Of course, larger batch sizes have a tradeoff: latency increases which may be undesirable in real-time applications. Why do larger batches increase throughput... » read more

Self-aligned Fin Cut Last Patterning Scheme for Fin Arrays of 24nm Pitch and Beyond


In 5nm FinFET technology and beyond, SRAM cell size reduction to 6 tracks is required with a fin pitch of 24nm. Fin depopulation is mandatory to enable area scaling, but it becomes challenging at small pitches. In the first part of our study, we simulate a FinFET process flow with various fin cut approaches to obtain a 3D model of a FinFET SRAM device. Layout dependent effects on silicon and pr... » read more

More Memory And Processor Tradeoffs


Creating a new chip architecture is becoming an increasingly complex series of tradeoffs about memories and processing elements, but the benefits are not always obvious when those tradeoffs are being made. This used to be a fairly straightforward exercise when there was one processor, on-chip SRAM and off-chip DRAM. Fast forward to 7/5nm, where chips are being developed for AI, mobile ph... » 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

In-Memory Vs. Near-Memory Computing


New memory-centric chip technologies are emerging that promise to solve the bandwidth bottleneck issues in today’s systems. The idea behind these technologies is to bring the memory closer to the processing tasks to speed up the system. This concept isn’t new and the previous versions of the technology fell short. Moreover, it’s unclear if the new approaches will live up to their billi... » read more

Comparative Stochastic Process Variation Bands For N7, N5, And N3 At EUV


By Alessandro Vaglio Preta, Trey Gravesa, David Blankenshipa, Kunlun Baib, Stewart Robertsona, Peter De Bisschopc, John J. Biaforea a) KLA-Tencor Corporation, Austin, TX 78759, U.S.A. b) KLA-Tencor Corporation, Milpitas, CA 95035, U.S.A. c) IMEC, Kapeldreef 75, 3000, BE ABSTRACT Stochastics effects are the ultimate limiter of optical lithography technology and are a major concern for n... » read more

Pushing AI Into The Mainstream


Artificial intelligence is emerging as the driving force behind many advancements in technology, even though the industry has merely scratched the surface of what may be possible. But how deeply AI penetrates different market segments and technologies, and how quickly it pushes into the mainstream, depend on a variety of issues that still must be resolved. In addition to a plethora of techni... » read more

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