Fast speculative address generation and way caching for reducing L1 data cache energy

L1 data caches in high-performance processors continue to grow in set associativity. Higher associativity can significantly increase the cache energy consumption. Cache access latency can be affected as well, leading to an increase in overall energy consumption due to increased execution time. At the same time, the static energy consumption of the cache increases significantly with each new process generation. This paper proposes a new approach to reduce the overall L1 cache energy consumption using a combination of way caching and fast, speculative address generation. A 16-entry way cache storing a 3-bit way number for recently accessed L1 data cache lines is shown sufficient to significantly reduce both static and dynamic energy consumption of the L1 cache. Fast speculative address generation helps to hide the way cache access latency and is highly accurate. The L1 cache energy-delay product is reduced by 10% compared to using the way cache alone and by 37% compared to the use of multiple MRU technique.Peer ReviewedPostprint (published version

WatchPlant: Networked Bio-hybrid Systems for Pollution Monitoring of Urban Areas

[EN] Growing cities are a world-wide phenomenon and simultaneously awareness about potential dangers due to air pollution, heat, and pathogens is increasing. Integrated and permanent monitoring of environmental features in cities can help to establish an early warning system and to provide data for policy makers. In our new project `WatchPlant,¿ we propose a green approach for urban monitoring by a network of sensors tightly coupled with natural plants. We want to develop a sustainable, energy-efficient bio-hybrid system that harvests energy from living plants and utilizes methods of phytosensing, that is, using natural plants as sensors. We present our concept, here with focus on Alife-related methods operating on the gathered plant data and the bio-hybrid network. With a self-organizing network of sensors, that are alive, we hope to contribute to our future of livable green cities.Project WatchPlant has received funding from the European Union's Horizon 2020 research and innovation program under the FET grant agreement, no. 101017899. Project Biohybrids is funded by H2020 program, grant agreement no. 945773.Hamann, H.; Bogdan, S.; Diaz-Espejo, A.; García-Carmona, L.; Hernandez-Santana, V.; Kernbach, S.; Kernbach, A.... (2021). WatchPlant: Networked Bio-hybrid Systems for Pollution Monitoring of Urban Areas. MIT Press. 1-9. https://doi.org/10.1162/isal_a_003771

Biohybrid systems for environmental intelligence on living plants: WatchPlant project

[EN] New challenges such as climate change and sustainability arise in society influencing not only environmental issues but human's health directly. To face these new challenges IT technologies and their application to environmental intelligent monitoring become into a powerful tool to set new policies and blueprints to contribute to social good. In the new H2020 project, WatchPlant will provide new tools for environmental intelligence monitoring by the use of plants as "well-being" sensors of the environment they inhabit. This will be possible by equipping plants with a net of communicated wireless self-powered sensors, coupled with artificial intelligence (AI) to become plants into "biohybrid organisms" to test exposure-effects links between plant and the environment. It will become plants into a new tool to be aware of the environment status in a very early stage towards in-situ monitoring. Additionally, the system is devoted to be sustainable and energy-efficient thanks to the use of clean energy sources such as solar cells and a enzymatic biofuel cell (BFC) together with its self-deployment, self-awareness, adaptation, artificial evolution and the AI capabilities. In this concept paper, WatchPlant will envision how to face this challenge by joining interdisciplinary efforts to access the plant sap for energy harvesting and sensing purposes and become plants into "biohybrid organisms" to benefit social good in terms of environmental monitoring in urban scenarios.Project WatchPlant has received funding from the European Union¿s Horizon 2020 research and innovation program under the FET grant agreement, no. 101017899.García-Carmona, L.; Bogdan, S.; Diaz-Espejo, A.; Dobielewski, M.; Hamann, H.; Hernandez-Santana, V.; Kernbach, A.... (2021). Biohybrid systems for environmental intelligence on living plants: WatchPlant project. Association for Computing Machinery (ACM). 210-215. https://doi.org/10.1145/3462203.347588521021

Steering a Swarm of Large-Scale Underactuated Mechanical Systems Using a Generalized Coordinates Transformation

Steering large-scale particle or robot systems is challenging because of their high dimensionality. We use a centralized stochastic approach that allows for optimal control at the cost of a central element instead of a decentralized approach. Previous works are often restricted to the assumption of fully actuated robots. Here we propose an approach for underactuated robots that allows for energy-efficient control of the robot system. We consider a simple task of gathering the robots (minimizing positional variance) and steering them towards a goal point within a bounded area without obstacles. We make two main contributions. First, we present a generalized coordinate transformation for underactuated robots, whose physical properties should be considered. We choose Euler-Lagrange systems that describe a large class of robot systems. Second, we propose an optimal control mechanism with the prime objective of energy efficiency. We show the feasibility of our approach in robot simulations

A Swash Mass Pendulum with Passivity-Based Control

We propose a mechanical system named swash mass pendulum (SMP) with application in robotics, and we develop a passivity-based control approach. The SMP is a pendulum made of a rigid shaft connected to a pair of cross-shafts where four swash masses can move under the action of servo mechanisms. The control objective is to stabilize the pendulum at a desired rest orientation. The regulation at the desired orientation is obtained via energy shaping that prevents the solution of partial differential equations. The derivation of the control law consists of a) partial feedback linearization under input coupling, b) a proportional plus integral (PI) controller acting on two new passive outputs. The performance of the controller is assessed by both simulations and experimental results, showing the effectiveness of the control design for the novel proposed pendulum