Mixed SRAM And eDRAM Cell For Area And Energy-Efficient On-Chip AI Memory (Yale Univ.)


A new technical paper titled "MCAIMem: a Mixed SRAM and eDRAM Cell for Area and Energy-efficient on-chip AI Memory" was published by researchers at Yale University. Abstract: "AI chips commonly employ SRAM memory as buffers for their reliability and speed, which contribute to high performance. However, SRAM is expensive and demands significant area and energy consumption. Previous studies... » read more

The Uncertain Future Of In-Memory Compute


Experts at the Table — Part 2: Semiconductor Engineering sat down to talk about AI and the latest issues in SRAM with Tony Chan Carusone, chief technology officer at Alphawave Semi; Steve Roddy, chief marketing officer at Quadric; and Jongsin Yun, memory technologist at Siemens EDA. What follows are excerpts of that conversation. Part one of this conversation can be found here and part 3 is h... » read more

DRAM Choices Are Suddenly Much More Complicated


Chipmakers are beginning to incorporate multiple types and flavors of DRAM in the same advanced package, setting the stage for increasingly distributed memory but significantly more complex designs. Despite years of predictions that DRAM would be replaced by other types of memory, it remains an essential component in nearly all computing. Rather than fading away, its footprint is increasing,... » read more

SRAM In AI: The Future Of Memory


Experts at the Table — Part 1: Semiconductor Engineering sat down to talk about AI and the latest issues in SRAM with Tony Chan Carusone, CTO at Alphawave Semi; Steve Roddy, chief marketing officer at Quadric; and Jongsin Yun, memory technologist at Siemens EDA. What follows are excerpts of that conversation. Part two of this conversation can be found here and part three is here. [L-R]: ... » read more

SRAM-Based IMC For Cryogenic CMOS Using Commercial 5 nm FinFETs


A technical paper titled “Cryogenic In-Memory Computing for Quantum Processors Using Commercial 5-nm FinFETs” was published by researchers at University of Stuttgart, Indian Institute of Technology Kanpur, University of California Berkeley, and Technical University of Munich. Abstract: "Cryogenic CMOS circuits that efficiently connect the classical domain with the quantum world are the co... » read more

An Energy-Efficient 10T SRAM In-Memory Computing Macro Architecture For AI Edge Processor


A technical paper titled “An energy-efficient 10T SRAM in-memory computing macro for artificial intelligence edge processor” was published by researchers at Atal Bihari Vajpayee-Indian Institute of Information Technology and Management (ABV-IIITM). Abstract: "In-Memory Computing (IMC) is emerging as a new paradigm to address the von-Neumann bottleneck (VNB) in data-intensive applications.... » read more

Comparing Analog and Digital SRAM In-Memory Computing Architectures (KU Leuven)


A technical paper titled "Benchmarking and modeling of analog and digital SRAM in-memory computing architectures" was published by researchers at KU Leuven. Abstract: "In-memory-computing is emerging as an efficient hardware paradigm for deep neural network accelerators at the edge, enabling to break the memory wall and exploit massive computational parallelism. Two design models have surge... » read more

What Designers Need To Know About GAA


While only 12 years old, finFETs are reaching the end of the line. They are being supplanted by gate-all-around (GAA), starting at 3nm [1], which is expected to have a significant impact on how chips are designed. GAAs come in two main flavors today — nanosheets and nanowires. There is much confusion about nanosheets, and the difference between nanosheets and nanowires. The industry still ... » read more

Safeguarding SRAMs From IP Theft (Best Paper Award)


A technical paper titled "Beware of Discarding Used SRAMs: Information is Stored Permanently" was published by researchers at Auburn University. The paper won "Best Paper Award" at the IEEE International Conference on Physical Assurance and Inspection of Electronics (PAINE) Oct. 25-27 in Huntsville. Abstract: "Data recovery has long been a focus of the electronics industry for decades by s... » read more

Scalable Optical AI Accelerator Based on a Crossbar Architecture


A new technical paper titled "Scalable Coherent Optical Crossbar Architecture using PCM for AI Acceleration" was published by researchers at University of Washington. Abstract: "Optical computing has been recently proposed as a new compute paradigm to meet the demands of future AI/ML workloads in datacenters and supercomputers. However, proposed implementations so far suffer from lack of sc... » read more

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