ARCO - Microarquitectura i Compiladors
Les activitats de recerca del grup ARCO es centren en l'area de arquitectura de computadors, compiladors i el processament en paral·lel, amb especial èmfasi en la microarquitectura i les tècniques de generació de codi per a sistemes de computació fiables i eficients energèticament. Un dels seus principals enfocaments actuals és sobre sistemes de computació intel·ligents, on l'objectiu és dissenyar noves arquitectures per a l'aprenentatge automàtic, la visió per computador i el processament del llenguatge. L'altre enfocament principal és en els processadors gràfics tant per a càrregues de treball de propòsit general com per a aplicacions gràfiques.
El grup està format per professors i estudiants de la Universitat Politècnica de Catalunya, la Universitat de Múrcia i la Universitat Rovira i Virgili. El grup té un llarg historial de publicacions científiques, amb més de 500 articles d'investigació, i transferències de tecnologia, amb més de 50 patents.
Las actividades de investigación del grupo ARCO se centran en el área de arquitectura de computadores, compiladores y el procesamiento en paralelo, con especial énfasis en la microarquitectura y las técnicas de generación de código para sistemas de computación fiables y eficientes energéticamente. Uno de sus principales enfoques actuales es sobre sistemas de computación inteligentes, donde el objetivo es diseñar nuevas arquitecturas para el aprendizaje automático, la visión por computador y el procesamiento del lenguaje. El otro enfoque principal es en los procesadores gráficos tanto para cargas de trabajo de propósito general como para aplicaciones gráficas.
El grupo está formado por profesores y estudiantes de la Universidad Politécnica de Catalunya, la Universidad de Murcia y la Universidad Rovira i Virgili. El grupo tiene un largo historial de publicaciones científicas, con más de 500 artículos de investigación, y transferencias de tecnología, con más de 50 patentes.
The research activities of the ARCO group focus on computer architecture, compilers and parallel processing, with special emphasis on microarchitecture and code generation techniques for energy-efficient and reliable computing systems. One of its main current focuses is on intelligent computing systems, where the goal is to devise novel architectures for machine learning, computer vision, language processing. The other major focus is on graphics processors both for general-purpose and graphics workloads.
The group consists of faculty members and students from Polytechnic University of Catalonia, University of Murcia and Rovira i Virgili University. The group has a long track record of scientific publications, with more than 500 research papers, and technology transfers, with more than 50 patents.
The research activities of the ARCO group focus on computer architecture, compilers and parallel processing, with special emphasis on microarchitecture and code generation techniques for energy-efficient and reliable computing systems. One of its main current focuses is on intelligent computing systems, where the goal is to devise novel architectures for machine learning, computer vision, language processing. The other major focus is on graphics processors both for general-purpose and graphics workloads.
The group consists of faculty members and students from Polytechnic University of Catalonia, University of Murcia and Rovira i Virgili University. The group has a long track record of scientific publications, with more than 500 research papers, and technology transfers, with more than 50 patents.
Collections in this community
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Articles de revista [68]
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Reports de recerca [11]
Recent Submissions
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Lightweight register file caching in collector units for GPUs
(Association for Computing Machinery (ACM), 2023)
Conference report
Open AccessModern GPUs benefit from a sizable Register File (RF) to provide fine-grained thread switching. As the RF is huge and accessed frequently, it consumes a considerable share of the dynamic energy of the GPU. Designing a ... -
Simple out of order core for GPGPUs
(Association for Computing Machinery (ACM), 2023)
Conference report
Open AccessGPU architectures have become popular for executing general-purpose programs which rely on having a large number of threads that run concurrently to hide the latency among dependent instructions. This approach has an ... -
SHARP: An adaptable, energy-efficient accelerator for recurrent neural networks
(Association for Computing Machinery (ACM), 2023-01-24)
Article
Open AccessThe effectiveness of Recurrent Neural Networks (RNNs) for tasks such as Automatic Speech Recognition has fostered interest in RNN inference acceleration. Due to the recurrent nature and data dependencies of RNN computations, ... -
A survey of near-data processing architectures for neural networks
(2022-01-17)
Article
Open AccessData-intensive workloads and applications, such as machine learning (ML), are fundamentally limited by traditional computing systems based on the von-Neumann architecture. As data movement operations and energy consumption ... -
LOCATOR: Low-power ORB accelerator for autonomous cars
(Elsevier, 2023-04)
Article
Open AccessSimultaneous Localization And Mapping (SLAM) is crucial for autonomous navigation. ORB-SLAM is a state-of-the-art Visual SLAM system based on cameras used for self-driving cars. In this paper, we propose a high-performance, ... -
Triangle Dropping: An occluded-geometry predictor for energy-efficient mobile GPUs
(Association for Computing Machinery (ACM), 2022-09)
Article
Open AccessThis article proposes a novel micro-architecture approach for mobile GPUs aimed at early removing the occluded geometry in a scene by leveraging frame-to-frame coherence, thus reducing the overall energy consumption. Mobile ... -
Sliding window support for image processing in autonomous vehicles
(2022)
Conference report
Open AccessCamera-based autonomous driving extensively ma-nipulates images for object detection, object tracking, or camera-based localization tasks. Therefore, efficient and fast image processing is crucial in those systems. ... -
DTexL: Decoupled raster pipeline for texture locality
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
Conference report
Open AccessContemporary GPU architectures have multiple shader cores and a scheduler that distributes work (threads) among them, focusing on load balancing. These load balancing techniques favor thread distributions that are detrimental ... -
Irregular accesses reorder unit: improving GPGPU memory coalescing for graph-based workloads
(2023-01)
Article
Open AccessGPGPU architectures have become the dominant platform for massively parallel workloads, delivering high performance and energy efficiency for popular applications such as machine learning, computer vision or self-driving ... -
E-BATCH: Energy-efficient and high-throughput RNN batching
(2022-03)
Article
Open AccessRecurrent Neural Network (RNN) inference exhibits low hardware utilization due to the strict data dependencies across time-steps. Batching multiple requests can increase throughput. However, RNN batching requires a large ... -
CREW: Computation reuse and efficient weight storage for hardware-accelerated MLPs and RNNs
(2022-08-01)
Article
Open AccessDeep Neural Networks (DNNs) have achieved tremendous success for cognitive applications. The core operation in a DNN is the dot product between quantized inputs and weights. Prior works exploit the weight/input repetition ... -
Vector extensions in COTS processors to increase guaranteed performance in real-time systems
(2023-03)
Article
Open AccessThe need for increased application performance in high-integrity systems like those in avionics is on the rise as software continues to implement more complex functionalities. The prevalent computing solution for future ...
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