Author's Latest Posts


In-Memory Computing: Assessing Multilevel RRAM-Based VMM Operations


A new technical paper titled "Experimental Assessment of Multilevel RRAM-Based Vector-Matrix Multiplication Operations for In-Memory Computing" was published by researchers at IHP (the Leibniz Institute for High Performance Microelectronics). Abstract: "Resistive random access memory (RRAM)-based hardware accelerators are playing an important role in the implementation of in-memory computin... » read more

A RISC-V On-Chip Parallel Power Controller for HPC (ETH Zurich, U. of Bologna)


A new technical paper titled "ControlPULP: A RISC-V On-Chip Parallel Power Controller for Many-Core HPC Processors with FPGA-Based Hardware-In-The-Loop Power and Thermal Emulation" was published (preprint) by researchers at ETH Zurich and University of Bologna. Abstract (partial) "High-Performance Computing (HPC) processors are nowadays integrated Cyber-Physical Systems demanding complex an... » read more

Formal Processor Model Providing Secure Speculation For The Constant-Time Policy


A technical paper titled "ProSpeCT: Provably Secure Speculation for the Constant-Time Policy (Extended version)" was published by researchers at imec-DistriNet at KU Leuven, CEA, List, Université Paris Saclay and INRIA. Abstract: "We propose ProSpeCT, a generic formal processor model providing provably secure speculation for the constant-time policy. For constant-time programs under a no... » read more

ISA and Microarchitecture Extensions Over Dense Matrix Engines to Support Flexible Structured Sparsity for CPUs (Georgia Tech, Intel Labs)


A technical paper titled "VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs" was published (preprint) by researchers at Georgia Tech and Intel Labs. Abstract: "Deep Learning (DL) acceleration support in CPUs has recently gained a lot of traction, with several companies (Arm, Intel, IBM) announcing products with specialized matrix engines accessible v... » read more

Solid-State Electrochemical Thermal Transistor Without Using Liquid


A new technical paper titled "Solid-State Electrochemical Thermal Transistors" was published by researchers at Hokkaido University, Pusan National University, and the University of Tokyo. Abstract "Thermal transistors that electrically control heat flow have attracted growing attention as thermal management devices and phonon logic circuits. Although several thermal transistors are demons... » read more

Review Paper: Negative Capacitance GAA-FET


A new technical paper titled "Recent Developments in Negative Capacitance Gate-All-Around Field Effect Transistors: A Review" by researchers at PKU-HKUST Shenzhen-Hong Kong Institution and Shenzhen Institute of Peking University. "The novel device structure of negative capacitance gate all around field effect transistor (NC GAA-FET) can combine both the advantages of GAA-FET and NC-FET, and ... » read more

Measuring 3D Sidewall Topography & LER for Photoresist Patterns Using Tip-Tilting AFM Technology


A new technical paper titled "Enhancing the precision of 3D sidewall measurements of photoresist using atomic force microscopy with a tip-tilting technique" by researchers at National Metrology Institute of Japan (NMIJ) and National Institute of Advanced Industrial Science and Technology (AIST). "We have developed a technique for measuring the sidewall of the resist pattern using atomic for... » read more

HW-SW Co-Design Solution For Building Side-Channel-Protected ML Hardware


A technical paper titled "Hardware-Software Co-design for Side-Channel Protected Neural Network Inference" was published (preprint) by researchers at North Carolina State University and Intel. Abstract "Physical side-channel attacks are a major threat to stealing confidential data from devices. There has been a recent surge in such attacks on edge machine learning (ML) hardware to extract the... » read more

HBM-Enabled FPGA-Based Graph Processing Accelerator


A technical paper titled "ACTS: A Near-Memory FPGA Graph Processing Framework" was published by researchers at University of Virginia and Samsung. Abstract: "Despite the high off-chip bandwidth and on-chip parallelism offered by today's near-memory accelerators, software-based (CPU and GPU) graph processing frameworks still suffer performance degradation from under-utilization of available ... » read more

Review of Tools & Techniques for DL Edge Inference


A new technical paper titled "Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review" was published in "Proceedings of the IEEE" by researchers at University of Missouri and Texas Tech University. Abstract: Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted in breakthroughs in many areas. However, deploying thes... » read more

← Older posts Newer posts →