CAP - Grup de Computació d'Altes Prestacions
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.
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Articles de revista [343]
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Recent Submissions
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Task-based programming models for heterogeneous recurrent workloads
(Springer Nature, 2021)
Conference report
Open AccessThis 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
(2021-08-13)
Article
Open AccessThe 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
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Article
Open AccessProcessing 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
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference report
Open AccessStatistics 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)
(Escola Universitària Politècnica de Vilanova i la Geltrú, 2001)
Conference report
Restricted access - publisher's policyAprendizaje 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
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference report
Open AccessModern 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
(2021)
Article
Open AccessAll 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
(2021-03)
Article
Open AccessOne 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
(IEEE, 2021)
Conference report
Open AccessThe 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
(2021-07)
Article
Open AccessDisaggregation 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
(IEEE, 2021)
Conference report
Open AccessEmbedded 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
(Association for Computing Machinery (ACM), 2021)
Conference report
Open AccessDeep 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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