Person: Sáez Alcaide, Juan Carlos
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First Name
Juan Carlos
Last Name
Sáez Alcaide
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Informática
Department
Arquitectura de Computadores y Automática
Area
Arquitectura y Tecnología de Computadores
Identifiers
5 results
Search Results
Now showing 1 - 5 of 5
Item LFOC+: A Fair OS-Level Cache-Clustering Policy for Commodity Multicore Systems(IEEE Transactions on Computers, 2022) Sáez Alcaide, Juan Carlos; Castro Rodríguez, Fernando; Fanizzi, Graziano; Prieto Matías, ManuelCommodity multicore systems are increasingly adopting hardware support that enables the system software to partition the last-level cache (LLC). This support makes it possible for the operating system (OS) or the Virtual Machine Monitor (VMM) to mitigate shared-resource contention effects on multicores by assigning different co-running applications to various cache partitions. Recently cache-clustering (or partition-sharing) strategies have emerged as a way to improve system throughput and fairness on new platforms with cache-partitioning support. As opposed to strict cache-partitioning, which allocates separate cache partitions to each application, cache-clustering allows partitions to be shared by a group of applications. In this article we propose LFOC+, a fairness-aware OS-level cache-clustering policy for commodity multicore systems. LFOC+ tries to mimic the behavior of the optimal cache-clustering solution for fairness, which we could obtain for different workload scenarios by using a simulation tool. Our dynamic cache-clustering strategy continuously gathers data fromperformancemonitoring counters to classify applications at runtime based on the degree of cache sensitivity and contentiousness, and effectively separates cache-sensitive applications fromaggressor programs to improve fairness,while providing acceptable system throughput.We implemented LFOC+ in the Linux kernel and evaluated it on a real systemfeaturing an Intel Skylake processor, wherewe compare its effectiveness to that of four previously proposed cache-clustering policies. Our experimental análisis reveals that LFOC+ constitutes a lightweight OS-level policy and improves fairness relative to two other state-of-the-art fairness-aware strategies –Dunn and LFOC–, by up to 22% and up to 20.6%, respectively, and by9% and 4.9%on average.Item LFOC: A Lightweight Fairness-Oriented Cache Clustering Policy for Commodity Multicores(2019) García García, Adrián; Sáez Alcaide, Juan Carlos; Castro Rodríguez, Fernando; Prieto Matías, ManuelMulticore processors constitute the main architecture choice for modern computing systems in different market segments. Despite their benefits, the contention that naturally appears when multiple applications compete for the use of shared resources among cores, such as the last-level cache (LLC), may lead to substantial performance degradation. This may have a negative impact on key system aspects such as throughput and fairness. Assigning the various applications in the workload to separate LLC partitions with possibly different sizes, has been proven effective to mitigate shared-resource contention effects. In this article we propose LFOC, a clustering-based cache partitioning scheme that strives to deliver fairness while providing acceptable system throughput. LFOC leverages the Intel Cache Allocation Technology (CAT), which enables the system software to divide the LLC into different partitions. To accomplish its goals, LFOC tries to mimic the behavior of the optimal cache-clustering solution, which we could approximate by means of a simulator in different scenarios. To this end, LFOC effectively identifies streaming aggressor programs and cache sensitive applications, which are then assigned to separate cache partitions. We implemented LFOC in the Linux kernel and evaluated it on a real system featuring an Intel Skylake processor, where we compare its effectiveness to that of two state-of-the-art policies that optimize fairness and throughput, respectively. Our experimental analysis reveals that LFOC is able to bring a higher reduction in unfairness by leveraging a lightweight algorithm suitable for adoption in a real OS.- Project number: 38
Item Metodología de internacionalización de material docente basada en el uso de Markdown y Pandoc(2018) Sáez Alcaide, Juan Carlos; Sánchez-Elez Martín, Marcos; Risco Martín, José Luis; Castro Rodríguez, Fernando; Prieto Matías, Manuel; Sáez Puche, Regino; Chaver Martínez, Daniel; Olcoz Herrero, Katzalin; Clemente Barreira, Juan Antonio; Igual Peña, Francisco; García García, Adrián; Sánchez Foces, DavidLa internacionalización de la docencia ofrece grandes oportunidades para la Universidad, pero también plantea retos significativos para estudiantes y profesores. En particular, la creación y mantenimiento efectivo del material docente de una asignatura impartida simultáneamente en varios idiomas y con alto grado de coordinación entre los distintos grupos de la misma (p.ej., examen final/prácticas comunes para todos los estudiantes) puede suponer un importante desafío para los profesores. Para hacer frente a este problema, hemos diseñado una estrategia específica para la creación y gestión de material docente en dual (p.ej., inglés-español), y desarrollado un conjunto de herramientas multiplataforma para ponerla en práctica. La idea general es mantener en un mismo fichero de texto el contenido del documento que se desee construir en ambos idiomas, proporcionando justo detrás de cada párrafo y título en uno de los idiomas su traducción al otro idioma, empleando delimitadores especiales. Para crear estos documentos duales se emplea Markdown, un lenguaje de marcado ligero, que dada su sencillez y versatilidad está teniendo una rápida adopción por un amplio espectro de profesionales: desde escritores de novelas o periodistas, hasta administradores de sitios web. A partir de los documentos duales creados con Markdown, es posible generar automáticamente el documento final para cada idioma en el formato deseado que se pondrá a disposición de los estudiantes. Para esta tarea, nos basamos en el uso de la herramienta Pandoc, que permite realizar la conversión de documentos Markdown a una gran cantidad de formatos, como PDF, docx (Microsoft Word), EPUB (libro electrónico) o HTML. Como parte de nuestro proyecto, hemos creado extensiones de Pandoc para permitir la creación de documentos duales en Markdown y para aumentar la expresividad de este lenguaje con construcciones comunmente utilizadas en documentos de carácter docente. Item Reuse detector: improving the management of STT-RAM SLLCs(The Computer Journal, 2018) Rodríguez Rodríguez, Roberto Alonso; Díaz, Javier; Castro Rodríguez, Fernando; Ibáñez, Pablo; Chaver Martínez, Daniel Ángel; Viñals, Víctor; Sáez Alcaide, Juan Carlos; Prieto Matías, Manuel; Piñuel Moreno, Luis; Monreal, Teresa; Llabería, José MaríaVarious constraints of Static Random Access Memory (SRAM) are leading to consider new memory technologies as candidates for building on-chip shared last-level caches (SLLCs). Spin-Transfer Torque RAM (STT-RAM) is currently postulated as the prime contender due to its better energy efficiency, smaller die footprint and higher scalability. However, STT-RAM also exhibits some drawbacks, like slow and energy-hungry write operations that need to be mitigated before it can be used in SLLCs for the next generation of computers. In this work, we address these shortcomings by leveraging a new management mechanism for STT-RAM SLLCs. This approach is based on the previous observation that although the stream of references arriving at the SLLC of a Chip MultiProcessor (CMP) exhibits limited temporal locality, it does exhibit reuse locality, i.e. those blocks referenced several times manifest high probability of forthcoming reuse. As such, conventional STT-RAM SLLC management mechanisms, mainly focused on exploiting temporal locality, result in low efficient behavior. In this paper, we employ a cache management mechanism that selects the contents of the SLLC aimed to exploit reuse locality instead of temporal locality. Specifically, our proposal consists in the inclusion of a Reuse Detector (RD) between private cache levels and the STT-RAM SLLC. Its mission is to detect blocks that do not exhibit reuse, in order to avoid their insertion in the SLLC, hence reducing the number of write operations and the energy consumption in the STT-RAM. Our evaluation, using multiprogrammed workloads in quad-core, eight-core and 16-core systems, reveals that our scheme reports on average, energy reductions in the SLLC in the range of 37–30%, additional energy savings in the main memory in the range of 6–8% and performance improvements of 3% (quadcore), 7% (eight-core) and 14% (16-core) compared with an STT-RAM SLLC baseline where no RD is employed. More importantly, our approach outperforms DASCA, the state-of-the-art STT-RAM SLLC management, reporting —depending on the specific scenario and the kind of applications used— SLLC energy savings in the range of 4–11% higher than those of DASCA, delivering higher performance in the range of 1.5–14% and additional improvements in DRAM energy consumption in the range of 2–9% higher than DASCA.Item Enabling performance portability of data-parallel OpenMP applications on asymmetric multicore processors(2020) Sáez Alcaide, Juan Carlos; Castro Rodríguez, Fernando; Prieto Matías, ManuelAsymmetric multicore processors (AMPs) couple high-performance big cores and low-power small cores with the same instruction-set architecture but different features, such as clock frequency or microarchitecture. Previous work has shown that asymmetric designs may deliver higher energy efficiency than symmetric multicores for diverse workloads. Despite their benefits, AMPs pose significant challenges to runtime systems of parallel programming models. While previous work has mainly explored how to efficiently execute task-based parallel applications on AMPs, via enhancements in the runtime system, improving the performance of unmodified data-parallel applications on these architectures is still a big challenge. In this work we analyze the particular case of loop-based OpenMP applications, which are widely used today in scientific and engineering domains, and constitute the dominant application type in many parallel benchmark suites used for performance evaluation on multicore systems. We observed that conventional loop-scheduling OpenMP approaches are unable to efficiently cope with the load imbalance that naturally stems from the different performance delivered by big and small cores. To address this shortcoming, we propose Asymmetric Iteration Distribution (AID), a set of novel loop-scheduling methods for AMPs that distribute iterations unevenly across worker threads to efficiently deal with performance asymmetry. We implemented AID in libgomp –the GNU OpenMP runtime system–, and evaluated it on two different asymmetric multicore platforms. Our analysis reveals that the AID methods constitute effective replacements of the static and dynamic methods on AMPs, and are capable of improving performance over these conventional strategies by up to 56% and 16.8%, respectively.