A Detailed Evaluation of A Production Server With High-End MRDIMM Main Memory (BSC, Micron, Intel, UPC)


A new technical paper, "Performance and Energy Benefits of MRDIMMs," was published by researchers at Barcelona Supercomputing Center, Universitat Politecnica de Catalunya, Micron and Intel Corporation. Abstract "Multiplexed Rank DIMMs (MRDIMMs) have recently emerged as memory devices that enable higher bandwidth without increasing DRAM chip frequencies. This paper presents a detailed perf... » read more

3D DRAM with CBA Technology (Georgia Tech)


A new technical paper, "System-Technology Co-Optimization of Bitline Routing and Bonding Pathways in Monolithic 3D DRAM Architectures," was published by researchers at Georgia Tech. Abstract "3D DRAM has emerged as a promising approach for continued density scaling, but its viability is limited by routing and hybrid bonding constraints to periphery, which may degrade sensing margin, laten... » read more

AI Workloads at the Edge: Ensuring Performance, Privacy, and Security


Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss why some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president a... » read more

Optimizing AI Workloads For Edge Computing


Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss how some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president an... » read more

Breaking The Compromise: Low Power And High Performance For The Intelligent Edge


By 2030, over 75 billion devices will be connected worldwide, each expected to think, learn, and respond instantly (Statista, IoT Connected Devices Forecast). The world is connecting faster than ever. With tens of billions of smart devices coming online, intelligence can no longer live in the cloud alone. Edge AI is emerging as the new frontier, bringing smarter, safer, and more res... » read more

Moving AI Workloads To The Edge


Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss how some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president an... » read more

Co-Optimizing GPU Architecture And SW To Enhance Edge Inference Performance (NVIDIA)


A new technical paper titled "EdgeReasoning: Characterizing Reasoning LLM Deployment on Edge GPUs" was published by researchers at NVIDIA. Abstract "Edge intelligence paradigm is increasingly demanded by the emerging autonomous systems, such as robotics. Beyond ensuring privacy-preserving operation and resilience in connectivity-limited environments, edge deployment offers significant energ... » read more

Photonics as a Carbon-Sustainable Solution for Next-Gen AI Hardware (Boston Univ., NY CREATES, Lightmatter, Cornell Tech)


A new technical paper titled "Photonics for sustainable AI" was published by researchers at Boston University, NY CREATES, Lightmatter and Cornell Tech. Abstract "The rising computational demands of Artificial Intelligence (AI) are driving a rapid surge in carbon emissions from the Information and Communications Technology (ICT) sector. Traditional CMOS-based computing is reaching its scali... » read more

Performance And Energy Characterization Of A Commercial Compute-in-SRAM Device (Cornell, USC, MIT, GSI)


A new technical paper titled "Characterizing and Optimizing Realistic Workloads on a Commercial Compute-in-SRAM Device" was published by researchers at Cornell University, USC, MIT and GSI Technology Inc. Abstract "Compute-in-SRAM architectures offer a promising approach to achieving higher performance and energy efficiency across a range of data-intensive applications. However, prior evalu... » read more

A Fundamental Rethinking Of Memory Hierarchy Design (Stanford University)


A new technical paper titled "The Future of Memory: Limits and Opportunities" was published by researchers at Stanford University and an independent researcher. Abstract "Memory latency, bandwidth, capacity, and energy increasingly limit performance. In this paper, we reconsider proposed system architectures that consist of huge (many-terabyte to petabyte scale) memories shared among large ... » read more

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