Wafer-Scale Computing for LLMs (U. of Edinburgh, Microsoft)


A new technical paper titled "WaferLLM: A Wafer-Scale LLM Inference System" was published by researchers at University of Edinburgh and Microsoft Research. Abstract "Emerging AI accelerators increasingly adopt wafer-scale manufacturing technologies, integrating hundreds of thousands of AI cores in a mesh-based architecture with large distributed on-chip memory (tens of GB in total) and ultr... » read more

Potential of Wireless Interconnects For Improving Performance And Flexibility Of Multi-Chip AI Accelerators


A new technical paper titled "Exploring the Potential of Wireless-enabled Multi-Chip AI Accelerators" was published by researchers at Universitat Politecnica de Catalunya. Abstract "The insatiable appetite of Artificial Intelligence (AI) workloads for computing power is pushing the industry to develop faster and more efficient accelerators. The rigidity of custom hardware, however, conflict... » read more

Power Delivery Challenges in 3D HI CIM Architectures for AI Accelerators (Georgia Tech)


A new technical paper titled "Co-Optimization of Power Delivery Network Design for 3D Heterogeneous Integration of RRAM-based Compute In-Memory Accelerators" was published by researchers at Georgia Tech. Abstract: "3D heterogeneous integration (3D HI) offers promising solutions for incorporating substantial embedded memory into cutting-edge analog compute-in-memory (CIM) AI accelerators, ad... » read more

Transistor Sizing Approach for OTA Circuits Using a Transformer Architecture


A  new technical paper titled "Accelerating OTA Circuit Design: Transistor Sizing Based on a Transformer Model and Precomputed Lookup Tables" was published by University Minnesota and Cadence. Abstract: "Device sizing is crucial for meeting performance specifications in operational transconductance amplifiers (OTAs), and this work proposes an automated sizing framework based on a transform... » read more

Optimization of Oxygen Plasma Conditions for Cu-Cu Bonding


A new technical paper titled "Understanding and Optimizing Oxygen Plasma Treatment for Enhanced Cu-Cu Bonding Application" was published by researchers at Seoul National University of Science and Technology. Abstract "This study investigates the optimization of O2 plasma treatment conditions to enhance Cu-Cu bonding. The O2 plasma treatment conditions were optimized using Design of Experime... » read more

Indium Tungsten Oxide (IWO) Thin-Film Transistors


A new technical paper titled "Thermally Dependent Metastability of Indium-Tungsten-Oxide Thin-Film Transistors" was published by researchers at Rochester Institute of Technology and Corning Research and Development Corporation. Abstract "Indium tungsten oxide (IWO) has been investigated as an oxide semiconductor candidate for next-generation thin-film transistors (TFTs). Bottom-gate TFTs we... » read more

Optimization of the Inter-Chiplet Interconnect And The Chiplet Placement (ETH Zurich, U. of Bologna)


A new technical paper titled "PlaceIT: Placement-based Inter-Chiplet Interconnect Topologies" was published by researchers at ETH Zurich and University of Bologna. Abstract "2.5D integration technology is gaining traction as it copes with the exponentially growing design cost of modern integrated circuits. A crucial part of a 2.5D stacked chip is a low-latency and high-throughput inter-ch... » read more

Indium Nitrate As An Advanced Metal-Oxide Resist for EUV Lithography


A new technical paper titled "Sensitivity and contrast of indium nitrate hydrate resist evaluated by low-energy electron beam and extreme ultraviolet exposure" was published by researchers at UT Dallas. "We evaluate the sensitivity and contrast of indium nitrate resists by analyzing dose curves collected using electron beam lithography (EBL) and extreme ultraviolet (EUV) exposure, " states t... » read more

Mixed-Precision DL Inference, Co-Designed With HW Accelerator DPU (Intel)


A new technical paper titled "StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign" was published by Intel. Abstract "In this paper, we propose StruM, a novel structured mixed-precision-based deep learning inference method, co-designed with its associated hardware accelerator (DPU), to address the escalating computational and memory demands of deep learning worklo... » read more

Processing-Using-DRAM: Attaining High-Performance Via Dynamic Precision Bit-Serial Arithmetic (ETH Zurich, et al.)


A new technical paper titled "Proteus: Achieving High-Performance Processing-Using-DRAM via Dynamic Precision Bit-Serial Arithmetic" was published by researchers at ETH Zurich, Cambridge University, Universidad de Córdoba, Univ. of Illinois Urbana-Champaign and NVIDIA Research. Abstract "Processing-using-DRAM (PUD) is a paradigm where the analog operational properties of DRAM structures ... » read more

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