Research
X-HEEP: An Open-Source, Configurable and Extendible RISC-V Platform for TinyAI Applications
Abstract
X-HEEP is an open-source, configurable RISC-V platform specifically designed for ultra-low-power edge applications (TinyAI). Its key innovation is the eXtendible Accelerator InterFace (XAIF), which enables seamless, highly
Research
Targeted Wearout Attacks in Microprocessor Cores
Originally published on ArXiv - Hardware Architecture
Computer Science > Cryptography and Security
arXiv:2508.16868v1 (cs)
[Submitted on 23 Aug 2025]
Title:Targeted Wearout Attacks in Microprocessor Cores
Authors:Joshua Mashburn, Johann Knechtel,
Research
Bare-Metal RISC-V + NVDLA SoC for Efficient Deep Learning Inference
Abstract
This paper introduces a novel System-on-Chip (SoC) architecture that tightly couples a 32-bit Codasip uRISC_V core with the open-source NVDLA for efficient deep learning inference on edge
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Neural Network Quantization for Microcontrollers: A Comprehensive Survey of Methods, Platforms, and Applications
Abstract
This comprehensive survey addresses the challenges of deploying Quantized Neural Networks (QNNs) on resource-constrained microcontrollers (MCUs) within the TinyML paradigm. It systematically reviews hardware-oriented quantization methods, focusing on the critical
Research
VTR 9: Open-Source CAD for Fabric and Beyond FPGA Architecture Exploration
Abstract
VTR 9 represents a significant advancement in the open-source Verilog-to-Routing CAD flow, focusing on enabling comprehensive exploration of next-generation reconfigurable architectures. This release introduces powerful modeling capabilities for
Research
IzhiRISC-V -- a RISC-V-based Processor with Custom ISA Extension for Spiking Neuron Networks Processing with Izhikevich Neurons
Abstract
This paper presents IzhiRISC-V, a specialized RISC-V-compliant processor engineered to overcome the inherent inefficiency of running Spiking Neural Networks (SNNs) on general-purpose hardware. The core innovation is a