Chip Industry’s Technical Paper Roundup: Oct. 4


New technical papers added to Semiconductor Engineering’s library this week. [table id=55 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit for... » read more

Adaptive Memristive Hardware


A new technical paper titled "Self-organization of an inhomogeneous memristive hardware for sequence learning" was just published by researchers at University of Zurich, ETH Zurich, Université Grenoble Alpes, CEA, Leti and Toshiba. "We design and experimentally demonstrate an adaptive hardware architecture Memristive Self-organizing Spiking Recurrent Neural Network (MEMSORN). MEMSORN incorp... » read more

Decreasing Refresh Latency of Off-the-Shelf DRAM Chips


A new technical paper titled "HiRA: Hidden Row Activation for Reducing Refresh Latency of Off-the-Shelf DRAM Chips" was published by researchers at ETH Zürich, TOBB University of Economics and Technology and Galicia Supercomputing Center (CESGA). Abstract "DRAM is the building block of modern main memory systems. DRAM cells must be periodically refreshed to prevent data loss. Refresh oper... » read more

Technical Paper Roundup: Sept 27


New technical papers added to Semiconductor Engineering’s library this week. [table id=53 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit f... » read more

Research Bits: Sept. 20


Multi-mode memristors Researchers from ETH Zurich, the University of Zurich, and Empa built a new memristor that can operate in multiple modes and could potentially be used to mimic neurons in more applications. “There are different operation modes for memristors, and it is advantageous to be able to use all these modes depending on an artificial neural network’s architecture,” said R... » read more

Setting The Memory Controller Free From Managing DRAM Maintenance Ops (ETH Zurich)


A new technical paper titled "A Case for Self-Managing DRAM Chips: Improving Performance, Efficiency, Reliability, and Security via Autonomous in-DRAM Maintenance Operations" was published by researchers at ETH Zurich. Abstract: "The rigid interface of current DRAM chips places the memory controller completely in charge of DRAM control. Even DRAM maintenance operations, which are used to en... » read more

Technical Paper Round-Up: Aug 23


New technical papers added to Semiconductor Engineering’s library this week. [table id=46 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit for... » read more

Polynesia, A Novel Hardware/Software Cooperative Design for In-Memory HTAP Databases


A team of researchers from ETH Zurich, Google and Univ. of Illinois Urbana-Champaign recently published a technical paper titled "Polynesia: Enabling High-Performance and Energy-Efficient Hybrid Transactional/Analytical Databases with Hardware/Software Co-Design". Abstract (partial) "We propose Polynesia, a hardware–software co-designed system for in-memory HTAP [hybrid transactional/anal... » read more

Technical Paper Round-up: August 8


New technical papers added to Semiconductor Engineering’s library this week. [table id=44 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit for... » read more

Low Power HW Accelerator for FP16 Matrix Multiplications For Tight Integration Within RISC-V Cores


This new technical paper titled "RedMulE: A Compact FP16 Matrix-Multiplication Accelerator for Adaptive Deep Learning on RISC-V-Based Ultra-Low-Power SoCs" was published by researchers at University of Bologna and ETH Zurich. According to their abstract: "One of the key stumbling stones is the need for parallel floating-point operations, which are considered unaffordable on sub-100 mW extre... » read more

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