i-DPs CGRA: An Interleaved-Datapaths Reconfigurable Accelerator for Embedded Bio-signal Processing

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Radiant floor heating is widely recognized for its low-energy consumption and high efficiency. Traditional systems, however, typically heat the entire floor area within a space, conditioning spaces uniformly regardless of occupancy. This study investigates ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL. As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and ...

Particle accelerators are the drivers for large-scale research infrastructures for particle physics but also for many branches of condensed matter research. The types of accelerator-driven research infrastructures include particle colliders, neutron, muon ...

With the growth in the performance of general-purpose computing no longer following Moore's law and Dennard scaling, the use of hardware-specialized systems is common practice. Field-programmable gate arrays (FPGAs) are adopted in cloud and cyber-physical ...

A modular multiple frequency coils inductive link system to wirelessly provide power for at least a medical implant at an output of a receiving coil, whereby the receiving coil is configured to be implanted in an organism. The modular multiple frequency co ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

Magnonics is a research field that has gained an increasing interest in both the fundamental and applied sciences in recent years. This field aims to explore and functionalize collective spin excitations in magnetically ordered materials for modern informa ...

Nonlinear epsilon-near-zero (ENZ) nanodevices featuring vanishing permittivity and CMOS-compatibility are attractive solutions for large-scale-integrated systems-on-chips. Such confined systems with unavoidable heat generation impose critical challenges fo ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

In this work, we propose an open-hardware low-power coarse-grained reconfigurable array connected to a lightweight microcontroller and enclosed in an application mapping framework. The latter provides complete support to configure kernels in the reconfigur ...

Field-programmable gate arrays (FPGAs) have become critical components in many cloud computing platforms. These devices possess the fine-grained parallelism and specialization needed to accelerate applications ranging from machine learning to networking an ...

The demise of Moore's Law and Dennard scaling has resulted in diminishing performance gains for general-purpose processors, and so has prompted a surge in academic and commercial interest for hardware accelerators. Specialized hardware has already redefine ...

Random Fourier features (RFFs) provide a promising way for kernel learning in a spectral case. Current RFFs-based kernel learning methods usually work in a two-stage way. In the first-stage process, learn-ing an optimal feature map is often formulated as a ...

Embedded systems confront two opposite goals: low-power operation and high performance. The current trend to reach these goals is toward heterogeneous platforms, including multi-core architectures with heterogeneous cores and hardware accelerators. The lat ...

Event-based sensors have the potential to optimize energy consumption at every stage in the signal processing pipeline, including data acquisition, transmission, processing, and storage. However, almost all state-of-the-art systems are still built upon th ...

The evolution of electronics has largely relied on downscaling to meet the continuous needs for faster and highly integrated devices(1). As the channel length is reduced, however, classic electronic devices face fundamental issues that hinder exploiting ma ...

The digital revolution has significantly transformed our world over the past decades, driven by the scaling of transistor dimensions and the exponential increase in computation power. However, as the CMOS scaling era approaches its end, the semiconductor i ...

i-DPs CGRA: An Interleaved-Datapaths Reconfigurable Accelerator for Embedded Bio-signal Processing

Chat with Graph Search

Modular Radiant Floor Heating and its Effect on Local Thermal Comfort

Secure Interface Design Leveraging Hardware/Software Support

Highly Parallel RTL Simulation

Energy-Efficient Particle Accelerators for Research

Electrical-Level Fault-Injection Attacks on FPGA-Based Systems

A modular multiple frequency inductive link to wirelessly power multiple miniaturized implants

EdgeAI-Aware Design of In-Memory Computing Architectures

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

The 2024 Magnonics Roadmap

Thermo-optic epsilon-near-zero effects

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

An Open-Hardware Coarse-Grained Reconfigurable Array for Edge Computing

A Visionary Look at the Security of Reconfigurable Cloud Computing

Building Chips Faster: Hardware-Compiler Co-Design for Accelerated RTL Simulation

End-to-end kernel learning via generative random Fourier features

Acceleration of Control Intensive Applications on Coarse-Grained Reconfigurable Arrays for Embedded Systems

An Error-Based Approximation Sensing Circuit for Event-Triggered Low-Power Wearable Sensors

Electronic metadevices for terahertz applications

Energy-Efficient Electronic Functions Based on the Co-integration of 2D and Ferroelectric Materials