En aquest grup s´investiga en tècniques que permeten millorar l´eficiència dels sistemes de computació d?altes prestacions. Aquest objectiu es tracta des de perspectives diverses que requereixen un cert grau de cooperació: arquitectura del sistema uniprocessador i multiprocessador, compilador, sistema operatiu, eines d´anàlisi, visualització i predicció, algorismes i aplicacions. Per mesurar l´eficiència es consideren mètriques que van més enllà del temps d´execució dels programes. En particular es consideren aspectes relacionats amb el disseny del sistema (cicle d´operació, àrea i consum de potència del processador i la jerarquia de memòria, escalabilitat de l´organització uniprocessador i multiprocessador), amb la verificació funcional dels sistemes, amb la facilitat i la portabilitat del model de programació i amb el rendiment en entorns multiprogramats i distribuïts, entre altres.

The group aims to improve the efficiency of high-performance computing systems. To that end, it employs a variety of approaches that require a certain level of cooperation and integration: microarchitecture and multiprocessor architecture, compilers, operating systems, analysis, visualisation and prediction tools, algorithms and applications. When measuring efficiency, in addition to the traditional approach that takes the execution time into account, we use metrics that consider design factors such as cycle time, area and power dissipation of the processor and memory hierarchy, scalability of the microarchitecture and multiprocessor organisation, system correctness, portability and ease of use of programming models, and performance when running on multiuser, multiprogrammed and distributed environments, among others.

The group aims to improve the efficiency of high-performance computing systems. To that end, it employs a variety of approaches that require a certain level of cooperation and integration: microarchitecture and multiprocessor architecture, compilers, operating systems, analysis, visualisation and prediction tools, algorithms and applications. When measuring efficiency, in addition to the traditional approach that takes the execution time into account, we use metrics that consider design factors such as cycle time, area and power dissipation of the processor and memory hierarchy, scalability of the microarchitecture and multiprocessor organisation, system correctness, portability and ease of use of programming models, and performance when running on multiuser, multiprogrammed and distributed environments, among others.

Recent Submissions

  • Task-based programming models for heterogeneous recurrent workloads 

    Bosch Pons, Jaume; Vidal, Miquel; Filgueras Izquierdo, Antonio; Jiménez González, Daniel; Álvarez Martínez, Carlos; Martorell Bofill, Xavier; Ayguadé Parra, Eduard (Springer Nature, 2021)
    Conference report
    Open Access
    This paper proposes the extension of task-based programming models with recurrent workloads concepts. The proposal introduces new clauses in the OmpSs task directive to efficiently model recurrent workloads. The clauses ...
  • NagareDB: A resource-efficient document-oriented time-series database 

    Garcia Calatrava, Carlos; Becerra Fontal, Yolanda; Cucchietti Tabanik, Fernando Martín; Diví Cuesta, Carla (2021-08-13)
    Article
    Open Access
    The recent great technological advance has led to a broad proliferation of Monitoring Infrastructures, which typically keep track of specific assets along time, ranging from factory machinery, device location, or even ...
  • Automatic distributed deep learning using resource-constrained edge devices 

    Gutiérrez Torre, Alberto; Bahadori, Kiyana; Baig, Shuja-ur-Rehman; Iqbal, Waheed; Vardanega, Tullio; Berral García, Josep Lluís; Carrera Pérez, David (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Article
    Open Access
    Processing data generated at high volume and speed from the Internet of Things, smart cities, domotic, intelligent surveillance, and e-healthcare systems require efficient data processing and analytics services at the Edge ...
  • SafeSU: an extended statistics unit for multicore timing interference 

    Cabo Pitarch, Guillem; Bas Jalón, Francisco; Lorenzo Ortega, Rubén; Trilla Rodríguez, David; Alcaide Portet, Sergi; Moreto Planas, Miquel; Hernández Luz, Carles; Abella Ferrer, Jaume (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Conference report
    Open Access
    Statistics units (SUs) in MPSoCs are becoming increasingly used for the (1) verification and (2) validation of multicore timing interference, as well as for (3) deploying safety measures in safety-related real-time systems. ...
  • Evaluación de la implantación del aprendizaje basado en proyectos en la EPSC (2001-2003) 

    Alcober Segura, Jesús Ángel; Ruiz Boqué, Sílvia; Valero García, Miguel (Escola Universitària Politècnica de Vilanova i la Geltrú, 2001)
    Conference report
    Restricted access - publisher's policy
    Aprendizaje basado en problemas o proyectos (a partir de ahora PBL) es el aprendizaje que se produce como resultado del esfuerzo que realiza el alumno para resolver un problema o llevar a cabo un proyecto. ...
  • Understanding power consumption and reliability of high-bandwidth memory with voltage underscaling 

    Nabavilarimi, Seyed Saber; Salami, Behzad; Unsal, Osman Sabri; Cristal Kestelman, Adrián; Sarbazi-Azad, Hamid; Mutlu, Onur (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Conference report
    Open Access
    Modern computing devices employ High-Bandwidth Memory (HBM) to meet their memory bandwidth requirements. An HBM-enabled device consists of multiple DRAM layers stacked on top of one another next to a compute chip (e.g, ...
  • Compiler-assisted compaction/restoration of SIMD instructions 

    Cebrián González, Juan Manuel; Balem, Thibaud; Barredo Ferreira, Adrián; Casas Guix, Marc; Moreto Planas, Miquel; Ros Bardisa, Alberto; Jimborean, Alexandra (2021)
    Article
    Open Access
    All the supercomputers in the world exploit data-level parallelism (DLP), for example by using single instructions to operate over several data elements. Improving vector processing is therefore key for exascale computing. ...
  • Size & shape matters: The need of HPC benchmarks of high resolution image training for deep learning 

    Parés Pont, Ferran; Megias Montsesinos, Pedro; García Gasulla, Dario; Garcia Gasulla, Marta; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José (2021-03)
    Article
    Open Access
    One of the purposes of HPC benchmarks is to identify limitations and bottlenecks in hardware. This functionality is particularly influential when assessing performance on emerging tasks, the nature and requirements of which ...
  • The UP2DATE baseline research platforms 

    Jover Álvarez, Álvaro; Calderón Torres, Alejandro Josué; Rodríguez Ferrández, Iván; Kosmidis, Leonidas; Asifuzzaman, Kazi; Uven, Patrick; Gruttner, Kim; Poggi, Tomaso; Agirre, Irune (IEEE, 2021)
    Conference report
    Open Access
    The UP2DATE H2020 project focuses on highperformance heterogeneous embedded platforms for critical systems. We will develop observability and controllability solutions to support online updates while ensuring safety and ...
  • Workload-aware placement strategies to leverage disaggregated resources in the datacenter 

    Call Barreiro, Aaron; Polo Bardés, Jorda; Carrera Pérez, David (2021-07)
    Article
    Open Access
    Disaggregation of resources is a datacenter strategy that aims to decouple the physical location of resources from the place where they are accessed, as opposed to physically attached devices connected to the Peripheral ...
  • GPU4S: Major project outcomes, lessons learnt and way forward 

    Kosmidis, Leonidas; Rodríguez Ferrández, Iván; Jover Álvarez, Álvaro; Alcaide Portet, Sergi; Lachaize, Jérôme; Notebaert, Olivier; Certain, Antoine; Steenari, David (IEEE, 2021)
    Conference report
    Open Access
    Embedded GPUs have been identified from both private and government space agencies as promising hardware technologies to satisfy the increased needs of payload processing. The GPU4S (GPU for Space) project funded from the ...
  • An oracle for guiding large-scale model/hybrid parallel training of convolutional neural networks 

    Njoroge Kahira, Albert; Nguyen, Truong Thao; Bautista Gomez, Leonardo; Takano, Ryousei; Badia Sala, Rosa Maria; Wahib, Mohamed (Association for Computing Machinery (ACM), 2021)
    Conference report
    Open Access
    Deep Neural Network (DNN) frameworks use distributed training to enable faster time to convergence and alleviate memory capacity limitations when training large models and/or using high dimension inputs. With the steady ...

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