171 research outputs found
La creació d'un hort : oportunitats per l'aprenentatge de les ciències
Creació d'un hortet per part d'alumnes de primà ria i secundà ria a partir del qual es realit-zen preguntes per tractar el currÃculum de Biologia i Geologia. Al mateix temps es fomenta el treball en equip, el respecte per la natura i la feina en el camp junt a introduir-los a la investigació basada en el mètode cientÃfic.Creation of a garden by primary and secondary students, through which several questions are made to study Biology and Geology curriculums. At the same time concepts such as team work, respect for nature and field labour are fostered, as well as connecting students to investigation based in the scientific method
Runtime home mapping for effective memory resource usage
In tiled Chip Multiprocessors (CMPs) last-level cache (LLC) banks are usually shared but distributed among the tiles. A static mapping of cache blocks to the LLC banks leads to poor efficiency since a block may be mapped away from the tiles actually accessing it. Dynamic policies either rely on the static mapping of blocks to a set of banks (D-NUCA) or rely on the OS to dynamically load pages to statically mapped addresses (first-touch).
In this paper, we propose Runtime Home Mapping (RHM), a new dynamic approach where the LLC home bank is determined at runtime by the memory controller when the block is fetched from main memory, trying to map each block as close as possible to the requestor thus speeding up execution time and lowering message latencies. Block migration and replication provide further improvements to basic RHM. Also, in a further optimization we eliminate the directory structure. All these optimizations involve specific NoC optimizations and co-designs. Results with PARSEC and SPLASH-2 applications show, when compared with alternative solutions, that RHM achieves a 41% and 35% average reduction in load and store latencies respectively compared to static mapping. This leads to an average reduction of 28% in applications execution.Lodde, M.; Flich Cardo, J. (2014). Runtime home mapping for effective memory resource usage. Microprocessors and Microsystems. 38(4):276-291. doi:10.1016/j.micpro.2014.03.008S27629138
CUTBUF: Buffer Management and Router Design for Traffic Mixing in VNET-Based NoCs
"© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works[EN] Router's buffer design and management strongly influence energy, area and performance of on-chip networks, hence it is crucial to encompass all of these aspects in the design process. At the same time, the NoC design cannot disregard preventing network-level and protocol-level deadlocks by devoting ad-hoc buffer resources to that purpose. In chip multiprocessor systems the coherence protocol usually requires different virtual networks (VNETs) to avoid deadlocks. Moreover, VNETutilization is highly unbalanced and there is no way to share buffers between them due to the need to isolate different traffic types. This paper proposes CUTBUF, a novel NoC router architecture to dynamically assign virtual channels (VCs) to VNETs depending on the actual VNETs load to significantly reduce the number of physical buffers in routers, thus saving area and power without decreasing NoC performance. Moreover, CUTBUF allows to reuse the same buffer for different traffic types while ensuring that the optimized NoC is deadlock-free both at network and protocol level. In this perspective, all the VCs are considered spare queues not statically assigned to a specific VNETand the coherence protocol only imposes a minimum number of queues to be implemented. Synthetic applications as well as real benchmarks have been used to validate CUTBUF, considering architectures ranging from 16 up to 48 cores. Moreover, a complete RTL router has been designed to explore area and power overheads. Results highlight how CUTBUF can reduce router buffers up to 33 percent with 2 percent of performance degradation, a 5 percent of operating frequency decrease and area and power saving up to 30.6 and 30.7 percent, respectively. Conversely, the flexibility of the proposed architecture improves by 23.8 percent the performance of the baseline NoC router when the same number of buffers is used.Zoni, D.; Flich Cardo, J.; Fornaciari, W. (2016). CUTBUF: Buffer Management and Router Design for Traffic Mixing in VNET-Based NoCs. IEEE Transactions on Parallel and Distributed Systems. 27(6):1603-1616. doi:10.1109/TPDS.2015.2468716S1603161627
An Efficient Implementation of Distributed Routing Algorithms for NoCs
The design of NoCs for multi-core chips introduces new design constraints like power consumption, area, and ul-tra low latencies. Although 2D meshes are preferred, het-erogeneous blocks, fabrication faults, reliability issues, and chip virtualization may lead to the need of irregular topolo-gies or regions. In this situation, efficient routing becomes a challenge. Although the use of routing tables at switches is flexible, it does not scale in terms of latency and area due to its memory requirements. LBDR (Logic-Based Distributed Routing) is proposed as a new routing method that removes the need of using rout-ing tables at all. LBDR enables the implementation of many routing algorithms on most of the practical topologies we might find in the near future in a multi-core system. From an initial topology and routing algorithm, a set of three bits per switch/output port is computed. Evaluation results show that, by using a small logic, LBDR mimics the performance of routing algorithms when implemented with routing ta-bles, both in regular and irregular topologies.
Area-efficient snoopy-aware NoC design for high-performance chip multiprocessor systems
Manycore CMP systems are expected to grow to tens or even hundreds of cores. In this paper we show that the effective co-design of both, the network-on-chip and the coherence protocol, improves performance and power meanwhile total area resources remain bounded. We propose a snoopy-aware network-on-chip topology made of two mesh-of-tree topologies. Reducing the complexity of the coherence protocol - and hence its resources - and moving this complexity to the network, leads to a global decrease in power consumption meanwhile area is barely affected. Benefits of our proposal are due to the high-throughput and low delay of the network, but also due to the simplicity of the coherence protocol. The proposed network and protocol minimizes communication amongst cores when compared to traditional solutions based either on 2D-mesh topologies or in directory-based protocols. (C) 2015 Elsevier Ltd. All rights reserved.Roca Pérez, A.; Hernández Luz, C.; Lodde, M.; Flich Cardo, J. (2015). Area-efficient snoopy-aware NoC design for high-performance chip multiprocessor systems. Computers and Electrical Engineering. 45:374-385. doi:10.1016/j.compeleceng.2015.04.020S3743854
Toward matrix multiplication for deep learning inference on the Xilinx Versal
The remarkable positive impact of Deep Neural Networks on many Artificial
Intelligence (AI) tasks has led to the development of various high performance
algorithms as well as specialized processors and accelerators. In this paper we
address this scenario by demonstrating that the principles underlying the
modern realization of the general matrix multiplication (GEMM) in conventional
processor architectures, are also valid to achieve high performance for the
type of operations that arise in deep learning (DL) on an exotic accelerator
such as the AI Engine (AIE) tile embedded in Xilinx Versal platforms. In
particular, our experimental results with a prototype implementation of the
GEMM kernel, on a Xilinx Versal VCK190, delivers performance close to 86.7% of
the theoretical peak that can be expected on an AIE tile, for 16-bit integer
operands.Comment: 11 page
Transient and Permanent Error Control for High-End Multiprocessor Systems-on-Chip
High-end MPSoC systems with built-in high-radix topologies achieve good performance because of the improved connectivity and the reduced network diameter. In high-end MPSoC systems, fault tolerance support is becoming a compulsory feature. In this work, we propose a combined method to address permanent and transient link and router failures in those systems. The LBDRhr mechanism is proposed to tolerate permanent link failures in some popular high-radix topologies. The increased router complexity may lead to more transient router errors than routers using simple XY routing algorithm. We exploit the inherent information redundancy (IIR) in LBDRhr logic to manage transient errors in the network routers. Thorough analyses are provided to discover the appropriate internal nodes and the forbidden signal patterns for transient error detection. Simulation results show that LBDRhr logic can tolerate all of the permanent failure combinations of long-range links and 80% of links failures at short-range links. Case studies show that the error detection method based on the new IIR extraction method reduces the power consumption and the residual error rate by 33% and up to two orders of magnitude, respectively, compared to triple modular redundancy. The impact of network topologies on the efficiency of the detection mechanism has been examined in this work, as well
La traducción feminista: comparación de dos traducciones al español de Alicia en el paÃs de las maravillas
Treball de Final de Grau en Traducció i Interpretació. Codi: TI0983. Curs acadèmic 2022/2023En este Trabajo de Fin de Grado (TFG), se exponen los dilemas a los que se
enfrentan los traductores y traductoras feministas junto con las técnicas de traducción
no sexista más representativas. Además, se analizan y comparan quince fragmentos de
las traducciones al español de Graciela Montes (Ediciones Colihue, 1996) y Joëlle
Eyheramonno (Edival, 1978) de Alicia en el PaÃs de las Maravillas para determinar si su
traducción se puede considerar libre de sexismo y, en caso contrario, aportar soluciones
alternativas de traducción.
Para ello, se resalta la importancia de la toma de conciencia por parte del
traductor o traductora para determinar si ciertos fragmentos del texto original no resultan
inclusivos para asà aplicar la técnica de traducción feminista correspondiente. Es por ello
que el intervencionismo conforma uno de los pilares de la traducción de género.
Una vez presentada la obra original, el autor y las dos traducciones, se lleva a
acabo el análisis de traducción, que consiste en la selección de quince fragmentos de
la obra con expresiones o términos potencialmente sexistas y la comparación de las
soluciones ofrecidas por las dos traductoras, además de algunas propuestas de
traducción personales en caso de que ninguna de las dos traducciones resulte
completamente inclusiva.
Finalmente, se exponen las conclusiones y resultados del análisis comparativo,
que desvelan que la traducción de Joëlle Eyheramonno resulta más adecuada desde
un punto de vista feminista, aunque en varios segmentos ambas presentan traducciones
con sesgos sexistas. Sin embargo, partiendo de la base de que nociones a favor de la
traducción feminista como translation as rewriting aún no habÃan aparecido, tiene
sentido pensar que las traducciones que se llevaban a cabo antaño, cuando los valores
del feminismo aún estaban emergiendo, carecÃan de conciencia feminista y hoy en dÃa
se traducirÃan de una forma muy diferente
HPC Platform for Railway Safety-Critical Functionalities Based on Artificial Intelligence
The automation of railroad operations is a rapidly growing industry. In 2023, a new European standard for the automated Grade of Automation (GoA) 2 over European Train Control System (ETCS) driving is anticipated. Meanwhile, railway stakeholders are already planning their research initiatives for driverless and unattended autonomous driving systems. As a result, the industry is particularly active in research regarding perception technologies based on Computer Vision (CV) and Artificial Intelligence (AI), with outstanding results at the application level. However, executing high-performance and safety-critical applications on embedded systems and in real-time is a challenge. There are not many commercially available solutions, since High-Performance Computing (HPC) platforms are typically seen as being beyond the business of safety-critical systems. This work proposes a novel safety-critical and high-performance computing platform for CV- and AI-enhanced technology execution used for automatic accurate stopping and safe passenger transfer railway functionalities. The resulting computing platform is compatible with the majority of widely-used AI inference methodologies, AI model architectures, and AI model formats thanks to its design, which enables process separation, redundant execution, and HW acceleration in a transparent manner. The proposed technology increases the portability of railway applications into embedded systems, isolates crucial operations, and effectively and securely maintains system resources.The novel approach presented in this work is being developed as a specific railway use case for autonomous train operation into SELENE European research project. This project has received funding from RIA—Research and Innovation action under grant agreement No. 871467
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