Automatically Generating Symbolic Prefetches for Distributed Transactional Memories

International audienceDeveloping efficient distributed applications while managing complexity can be challenging. Managing network latency is a key challenge for distributed applications. We propose a new approach to prefetching, symbolic prefetching, that can prefetch remote objects before their addresses are known. Our approach was designed to hide the latency of accessing remote objects in distributed transactional memory and a wide range of distributed object middleware frameworks. We present a static compiler analysis for the automatic generation of symbolic prefetches -- symbolic prefetches allow objects whose addresses are unknown to be prefetched. We evaluate this prefetching mechanism in the context of a middleware framework for distributed transactional memory. Our evaluation includes microbenchmarks, scientific benchmarks, and distributed benchmarks. Our results show that symbolic prefetching combined with caching can eliminate an average of 87% of remote reads. We measured speedups due to prefetching of up to 13.31× for accessing arrays and 4.54× for accessing linked lists

3rd Many-core Applications Research Community (MARC) Symposium. (KIT Scientific Reports ; 7598)

This manuscript includes recent scientific work regarding the Intel Single Chip Cloud computer and describes approaches for novel approaches for programming and run-time organization

(Fase 2) bajo minería de datos. Caso de estudio: MOTOS ELECTROMUEBLES- Departamento de Arauca

Motos Electromuebles es una empresa con 6 años de experiencia en el mercado Araucano, su actividad comercial consta de venta de repuestos para motos Honda y Hero, servicio de mantenimiento para motos; actualmente cuentan con cuatro sedes en el Departamento de Arauca: Arauca, Tame, Arauquita y Saravena. La empresa cuenta con un sistema transaccional web que almacena todos los registros de las diferentes dependencias. La siguiente propuesta presenta un diseño y desarrollo de un módulo CRM (Customer Relationship Management) adaptado a la empresa Motos Electromuebles de Arauca, aplicando un modelo de minería de datos. La minería de datos es un mecanismo para explorar grandes cantidades de datos y convertirlo en información, para este caso se utiliza para encaminar los datos que tiene la empresa de clientes, organizarla y lograr obtener la información que se solicita. Un CRM es una herramienta comercial y de marketing importante para cualquier empresa, se centra en la relación empresa - cliente. Es el pilar donde se centra la fidelización del cliente y se aplicará las acciones de mercadeo. En el estado del arte se consigna una definición precisa y clara de los dos conceptos ya que se requiere tener la definición clara para generar el análisis y el módulo con las estrategias de marketing. La base tecnológica para el desarrollo de la propuesta es el gestor de base de datos MYSQL y un lenguaje de programación PHP, se plantea la idea de desarrollo adecuado para esta empresa. Además se realiza una toma de requerimientos que se deberá utilizar para hacer la clasificación de los roles de acceso, manejo y clasificación de los clientes para que la empresa haga la toma de decisiones y ayudar a la gestión de ventas.Motos Electromuebles es una empresa con 6 años de experiencia en el mercado Araucano, su actividad comercial consta de venta de repuestos para motos Honda y Hero, servicio de mantenimiento para motos; actualmente cuentan con cuatro sedes en el Departamento de Arauca: Arauca, Tame, Arauquita y Saravena. La empresa cuenta con un sistema transaccional web que almacena todos los registros de las diferentes dependencias. La siguiente propuesta presenta un diseño y desarrollo de un módulo CRM (Customer Relationship Management) adaptado a la empresa Motos Electromuebles de Arauca, aplicando un modelo de minería de datos. La minería de datos es un mecanismo para explorar grandes cantidades de datos y convertirlo en información, para este caso se utiliza para encaminar los datos que tiene la empresa de clientes, organizarla y lograr obtener la información que se solicita. Un CRM es una herramienta comercial y de marketing importante para cualquier empresa, se centra en la relación empresa - cliente. Es el pilar donde se centra la fidelización del cliente y se aplicará las acciones de mercadeo. En el estado del arte se consigna una definición precisa y clara de los dos conceptos ya que se requiere tener la definición clara para generar el análisis y el módulo con las estrategias de marketing. La base tecnológica para el desarrollo de la propuesta es el gestor de base de datos MYSQL y un lenguaje de programación PHP, se plantea la idea de desarrollo adecuado para esta empresa. Además se realiza una toma de requerimientos que se deberá utilizar para hacer la clasificación de los roles de acceso, manejo y clasificación de los clientes para que la empresa haga la toma de decisiones y ayudar a la gestión de ventas

Efficient Communication and Synchronization on Manycore Processors

The increased number of cores integrated on a chip has brought about a number of challenges. Concerns about the scalability of cache coherence protocols have urged both researchers and practitioners to explore alternative programming models, where cache coherence is not a given. Message passing, traditionally used in distributed systems, has surfaced as an appealing alternative to shared memory, commonly used in multiprocessor systems. In this thesis, we study how basic communication and synchronization primitives on manycore processors can be improved, with an accent on taking advantage of message passing. We do this in two different contexts: (i) message passing is the only means of communication and (ii) it coexists with traditional cache-coherent shared memory. In the first part of the thesis, we analytically and experimentally study collective communication on a message-passing manycore processor. First, we devise broadcast algorithms for the Intel SCC, an experimental manycore platform without coherent caches. Our ideas are captured by OC-Bcast (on-chip broadcast), a tree-based broadcast algorithm. Two versions of OC-Bcast are presented: One for synchronous communication, suitable for use in high-performance libraries implementing the Message Passing Interface (MPI), and another for asynchronous communication, for use in distributed algorithms and general-purpose software. Both OC-Bcast flavors are based on one-sided communication and significantly outperform (by up to 3x) state-of-the-art two-sided algorithms. Next, we conceive an analytical communication model for the SCC. By expressing the latency and throughput of different broadcast algorithms through this model, we reveal that the advantage of OC-Bcast comes from greatly reducing the number of off-chip memory accesses on the critical path. The second part of the thesis focuses on lock-based synchronization. We start by introducing the concept of hybrid mutual exclusion algorithms, which rely both on cache-coherent shared memory and message passing. The hybrid algorithms we present, HybLock and HybComb, are shown to significantly outperform (by even 4x) their shared-memory-only counterparts, when used to implement concurrent counters, stacks and queues on a hybrid Tilera TILE-Gx processor. The advantage of our hybrid algorithms comes from the fact that their most critical parts rely on message passing, thereby avoiding the overhead of the cache coherence protocol. Still, we take advantage of shared memory, as shared state makes the implementation of certain mechanisms much more straightforward. Next, we try to profit from these insights even on processors without hardware support for message passing. Taking two classic x86 processors from Intel and AMD, we come up with cache-aware optimizations that improve the performance of executing contended critical sections by as much as 6x

Attribute-Level Versioning: A Relational Mechanism for Version Storage and Retrieval

Data analysts today have at their disposal a seemingly endless supply of data and repositories hence, datasets from which to draw. New datasets become available daily thus making the choice of which dataset to use difficult. Furthermore, traditional data analysis has been conducted using structured data repositories such as relational database management systems (RDBMS). These systems, by their nature and design, prohibit duplication for indexed collections forcing analysts to choose one value for each of the available attributes for an item in the collection. Often analysts discover two or more datasets with information about the same entity. When combining this data and transforming it into a form that is usable in an RDBMS, analysts are forced to deconflict the collisions and choose a single value for each duplicated attribute containing differing values. This deconfliction is the source of a considerable amount of guesswork and speculation on the part of the analyst in the absence of professional intuition. One must consider what is lost by discarding those alternative values. Are there relationships between the conflicting datasets that have meaning? Is each dataset presenting a different and valid view of the entity or are the alternate values erroneous? If so, which values are erroneous? Is there a historical significance of the variances? The analysis of modern datasets requires the use of specialized algorithms and storage and retrieval mechanisms to identify, deconflict, and assimilate variances of attributes for each entity encountered. These variances, or versions of attribute values, contribute meaning to the evolution and analysis of the entity and its relationship to other entities. A new, distinct storage and retrieval mechanism will enable analysts to efficiently store, analyze, and retrieve the attribute versions without unnecessary complexity or additional alterations of the original or derived dataset schemas. This paper presents technologies and innovations that assist data analysts in discovering meaning within their data and preserving all of the original data for every entity in the RDBMS