Review of Methods to Design Secure Memristor Computing Systems


A technical paper titled "Review of security techniques for memristor computing systems" was published by researchers at Israel Institute of Technology, Friedrich Schiller University Jena (Germany), and Leibniz Institute of Photonic Technology (IPHT). Abstract "Neural network (NN) algorithms have become the dominant tool in visual object recognition, natural language processing, and robotic... » read more

Security-Aware Compiler-Assisted Countermeasure to Mitigate Fault Attacks on RISC-V


A new technical paper titled "CompaSeC: A Compiler-Assisted Security Countermeasure to Address Instruction Skip Fault Attacks on RISC-V" was published by researchers at TU Munich and Fraunhofer Institute for Applied and Integrated Security (AISEC). Abstract "Fault-injection attacks are a risk for any computing system executing security-relevant tasks, such as a secure boot process. While ha... » read more

Index-Based Multi-Core BDD Package With Dynamic Memory Management & Reduced Fragmentation


A technical paper titled "EDDY: A Multi-Core BDD Package with Dynamic Memory Management and Reduced Fragmentation" was published by researchers at University of Bremen. ABSTRACT "In recent years, hardware systems have significantly grown in complexity. Due to the increasing complexity, there is a need to continuously improve the quality of the hardware design process. This leads designers t... » read more

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

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

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