Edge HW-SW Co-Design Platform Integrating RISC-V And HW Accelerators


A new technical paper titled "EigenEdge: Real-Time Software Execution at the Edge with RISC-V and Hardware Accelerators" was published by researchers at Columbia University. "We introduce a hardware/software co-design approach that combines software applications designed with Eigen, a powerful open-source C++ library that abstracts linear-algebra workloads, and real-time execution on heterog... » read more

EPFL’s Open Source Single-Core RISC-V Microcontroller for Edge Computing


A new technical paper titled "X-HEEP: An Open-Source, Configurable and Extendible RISC-V Microcontroller" was published by researchers at Ecole Polytechnique Fédérale de Lausanne (EPFL). Abstract: "In this work, we present eXtendible Heterogeneous Energy-Efficient Platform (X-HEEP), a configurable and extendible single-core RISC-V-based ultra-low-power microcontroller. X-HEEP can be used ... » read more

Working With The NimbleAI Project To Push The Boundaries Of Neuromorphic Vision


At the end of 2022, the EU kicked off a cool project that aims to implement neuromorphic vision. But what is that? Let’s take a deeper look at the project and our contribution. First, if you are not familiar with Codasip Labs, I want to mention this briefly. Codasip Labs is in fact our innovation hub where we explore new technologies and try to contribute to the technology of the future. ... » read more

RISC-V Vectorization And Potential for HPC


A new technical paper titled "Test-driving RISC-V Vector hardware for HPC" was published by researchers at University of Edinburgh. Abstract: "Whilst the RISC-V Vector extension (RVV) has been ratified, at the time of writing both hardware implementations and open source software support are still limited for vectorisation on RISC-V. This is important because vectorisation is crucial to obt... » read more

SW-HW Framework: Graphic Rendering on RISC-V GPUs (Georgia Tech, Cal Poly)


A new technical paper titled "Skybox: Open-Source Graphic Rendering on Programmable RISC-V GPUs" was published by researchers at Georgia Tech, California Polytechnic State University-San Luis Obispo. Abstract Excerpt: "In this work, we present Skybox, a full-stack open-source GPU architecture with integrated software, compiler, hardware, and simulation environment, that enables end-to-end G... » read more

RISC-V Driving New Verification Concepts


Semiconductor Engineering sat down to discuss gaps in tools and why new methodologies are needed for RISC-V processors, with Pete Hardee, group director for product management at Cadence; Mike Eftimakis, vice president for strategy and ecosystem at Codasip; Simon Davidmann, founder and CEO of Imperas Software; Sven Beyer, program manager for processor verification at Siemens EDA; Kiran Vittal, ... » read more

Scalable, Shared-L1-Memory Manycore RISC-V System


A new technical paper titled "MemPool: A Scalable Manycore Architecture with a Low-Latency Shared L1 Memory" was published by researchers at ETH Zurich and University of Bologna. Abstract: "Shared L1 memory clusters are a common architectural pattern (e.g., in GPGPUs) for building efficient and flexible multi-processing-element (PE) engines. However, it is a common belief that these tightly... » read more

Gem5 Simulation Environment With Customized RISC-V Instructions for LIM Architectures


A new technical paper titled "Simulation Environment with Customized RISC-V Instructions for Logic-in-Memory Architectures" was published by researchers at National Tsing-Hua University, Politecnico di Torino, University of Rome Tor Vergata, and University of Twente. Abstract "Nowadays, various memory-hungry applications like machine learning algorithms are knocking "the memory wall". Tow... » read more

Low-Power Heterogeneous Compute Cluster For TinyML DNN Inference And On-Chip Training


A new technical paper titled "DARKSIDE: A Heterogeneous RISC-V Compute Cluster for Extreme-Edge On-Chip DNN Inference and Training" was published by researchers at University of Bologna and ETH Zurich. Abstract "On-chip deep neural network (DNN) inference and training at the Extreme-Edge (TinyML) impose strict latency, throughput, accuracy, and flexibility requirements. Heterogeneous clus... » read more

What’s Required To Secure Chips


Experts at the Table: Semiconductor Engineering sat down to talk about how to verify that a semiconductor design will be secure, with Mike Borza, Synopsys scientist; John Hallman, product manager for trust and security at Siemens EDA; Pete Hardee, group director for product management at Cadence; Paul Karazuba, vice president of marketing at Expedera; and Dave Kelf, CEO of Breker Verification. ... » read more

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