En esta ocasión se trata de una entrada que habla de una conferencia virtual y en diferido: Como parte de mi preparación para el próximo viaje a Boston, he visto una conferencia de la Profesora Una-May O'Reilly en MIT-TV. Muy interesante su forma de presentar la charla, contándonos su vida y adaptando el nivel de la misma a la audiencia. En la charla hace un repaso de su vida, su historia, las diferentes alternativas que ha tenido en la vida y sus elecciones y luego pasa a hablar de como utilizar los ACO para generar Arte, sin que el artista sienta que no está creando.
Puedes ver la charla completa aquí
miércoles, 7 de noviembre de 2012
viernes, 21 de septiembre de 2012
UNA TÉCNICA PARA LA OPTIMIZACIÓN DE LOS PARÁMETROS DE INDICADORES TÉCNICOS BURSÁTILES MEDIANTE ALGORITMOS EVOLUTIVOS MULTI-OBJETIVO
Hace casi un año que no he recogido nada de las distintas charlas a las que he asistido, pero voy a retomar estas páginas con una Tesis de la que estoy muy orgulloso, la de Diego Bodas-Sagi, que he codirigido con Pablo Fernández Blanco. La defensa se produjo el pasado 20 de septiembre de 2012 en la Sala de Grados de la Facultad de Informática, de la Universidad Complutense de Madrid.
En esta tesis Se ha presentado la técnica Multi-Objective Technical Indicator Optimization iNitiative I (MOTION I) para la optimización de parámetros de indicadores técnicos bursátiles y así obtener recomendaciones de acción (comprar / vender / mantener) en inversiones en bolsa. Con esto se establecen las bases teóricas para la implementación de una herramienta de toma de decisiones de inversión en los mercados financieros. MOTION I es una técnica que:
En esta tesis Se ha presentado la técnica Multi-Objective Technical Indicator Optimization iNitiative I (MOTION I) para la optimización de parámetros de indicadores técnicos bursátiles y así obtener recomendaciones de acción (comprar / vender / mantener) en inversiones en bolsa. Con esto se establecen las bases teóricas para la implementación de una herramienta de toma de decisiones de inversión en los mercados financieros. MOTION I es una técnica que:
- Permite la escalabilidad de la estrategia de inversión: se puede aplicar a una gran variabilidad de mercados financieros e indicadores.
- Es adaptable al usuario: permite elegir el MOEA que se desea emplear así como introducir nuevos objetivos o modificar los propuestos en este trabajo.
- Realiza un proceso de optimización continuo por lo que se adapta mejor que otras técnicas a la variabilidad de los mercados bursátiles
martes, 18 de octubre de 2011
DiDi: Mitigating the Performance Impact of TLB Shootdowns Using a Shared TLB
Carlos Villavieja, UPC
@PACT 2011
Translation Lookaside Buffers (TLBs) are ubiquitously used in modern architectures to cache virtual-to-physical mappings and, as they are looked up on every memory access, are paramount to performance scalability. The emergence of chipmultiprocessors (CMPs) with per-core TLBs, has brought the problem of TLB coherence to front stage. TLBs are kept coherent at the software-level by the operating system (OS). Whenever the OS modifies page permissions in a page table, it must initiate a coherency transaction among TLBs,a process known as a TLB shootdown. Current CMPs rely on the OS to approximate the set of TLBs caching a mapping and synchronize TLBs using costly Inter-Proceessor Interrupts (IPIs) and software handlers. In this paper, we characterize the impact of TLB shootdowns on multiprocessor performance and scalability, and present the design of a scalable TLB coherency mechanism. First, we show that both TLB shootdown cost and frequency increase with the number of processors and project that softwarebased TLB shootdowns would thwart the performance of large multiprocessors. We then present a scalable architectural mechanism that couples a shared TLB directory with load/store queue support for lightweight TLB invalidation, and thereby eliminates the need for costly IPIs. Finally, we show that the proposed mechanism reduces the fraction of machine cycles wasted on TLB shootdowns by an order of magnitude.
Optimizing Data Layouts for Parallel Computation on Multicores
Yuanrui Zhang, Wei Ding, Jun Liu, and Mahmut Kandemir
The Pennsylvania State University
@PACT 2011
The emergence of multicore platforms offers several opportunities for boosting application performance. These opportunities, which include parallelism and data locality benefits,require strong support from compilers as well as operating systems. Current compiler research targeting multicores mostly focuses on code restructuring and mapping. In this work,we explore automatic data layout transformation targeting multithreaded applications running on multicores. Our transformation considers both data access patterns exhibited by different threads of a multithreaded application and the on chip cache topology of the target multicore architecture. It automatically determines a customized memory layout foreach target array to minimize potential cache conflicts acrossthreads. Our experiments show that, our optimization brings significant benefits over state-of-the-art data locality optimization strategies when tested using 30 benchmark programs on an Intel multicore machine. The results also indicate that this strategy is able to scale to larger core counts and it performs better with increased data set sizes.
The Pennsylvania State University
@PACT 2011
The emergence of multicore platforms offers several opportunities for boosting application performance. These opportunities, which include parallelism and data locality benefits,require strong support from compilers as well as operating systems. Current compiler research targeting multicores mostly focuses on code restructuring and mapping. In this work,we explore automatic data layout transformation targeting multithreaded applications running on multicores. Our transformation considers both data access patterns exhibited by different threads of a multithreaded application and the on chip cache topology of the target multicore architecture. It automatically determines a customized memory layout foreach target array to minimize potential cache conflicts acrossthreads. Our experiments show that, our optimization brings significant benefits over state-of-the-art data locality optimization strategies when tested using 30 benchmark programs on an Intel multicore machine. The results also indicate that this strategy is able to scale to larger core counts and it performs better with increased data set sizes.
Phase-Based Application-Driven Hierarchical Power Managementon the Single-chip Cloud Computer
Nikolas Ioannou @ PACT 2011
University of Edinburgh
To improve energy efficiency processors allow for Dynamic Voltage and Frequency Scaling (DVFS), which enables changing their performance and power consumption on-thefly.Many-core architectures, such as the Single-chip Cloud Computer (SCC) experimental processor from Intel Labs,have DVFS infrastructures that scale by having many more independent voltage and frequency domains on-die than today’smulti-cores.This paper proposes a novel, hierarchical, and transparent client-server power management scheme applicable to such architectures. The scheme tries to minimize energy consumption within a performance window taking into consideration not only the local information for cores within frequency domains but also information that spans multiple frequency and voltage domains.We implement our proposed hierarchical power control using a novel application-driven phase detection and prediction approach for Message Passing Interface (MPI) applications, a natural choice on the SCC with its fast on-chip network and its non-coherent memory hierarchy. This phase predictor operates as the front-end to the hierarchical DVFS controller,providing the necessary DVFS scheduling points.Experimental results with SCC hardware show that our approach provides significant improvement of the EnergyDelayProduct (EDP) of as much as 27.2%, and 11.4% on average,with an average increase in execution time of 7.7% over a baseline version without DVFS. These improvements come from both improved phase prediction accuracy and more effectiveDVFS control of the domains, compared to existing approaches.
University of Edinburgh
To improve energy efficiency processors allow for Dynamic Voltage and Frequency Scaling (DVFS), which enables changing their performance and power consumption on-thefly.Many-core architectures, such as the Single-chip Cloud Computer (SCC) experimental processor from Intel Labs,have DVFS infrastructures that scale by having many more independent voltage and frequency domains on-die than today’smulti-cores.This paper proposes a novel, hierarchical, and transparent client-server power management scheme applicable to such architectures. The scheme tries to minimize energy consumption within a performance window taking into consideration not only the local information for cores within frequency domains but also information that spans multiple frequency and voltage domains.We implement our proposed hierarchical power control using a novel application-driven phase detection and prediction approach for Message Passing Interface (MPI) applications, a natural choice on the SCC with its fast on-chip network and its non-coherent memory hierarchy. This phase predictor operates as the front-end to the hierarchical DVFS controller,providing the necessary DVFS scheduling points.Experimental results with SCC hardware show that our approach provides significant improvement of the EnergyDelayProduct (EDP) of as much as 27.2%, and 11.4% on average,with an average increase in execution time of 7.7% over a baseline version without DVFS. These improvements come from both improved phase prediction accuracy and more effectiveDVFS control of the domains, compared to existing approaches.
No More Backstabbing... A Faithful Scheduling Policy for Multithreaded Programs
PACT Conference 11 Octubre de 2011, 17:00 Spanish Time, Galveston Island TX, USA, Hotel Galvez.
Kishore Kumar Pusukuri, Rajiv Gupta, and Laxmi N. Bhuyan
Efficient contention management is the key to achieving scalable performance for multithreaded applications running on multicore systems. However, contention management policies provided by modern operating systems increase context-switches and lead to performance degradation for multithreaded applications under high loads. Moreover, this problem is exacerbated by the interaction between contention management policies and OS scheduling polices. Time Share(TS) is the default scheduling policy in a modern OS such as OpenSolaris and with TS policy, priorities of threads change very frequently for balancing load and providing fairness inscheduling. Due to the frequent ping-ponging of priorities, threads of an application are often preempted by the threads of the same application. This increases the frequency of involuntary context-switches as wells as lock-holder thread preemptions and leads to poor performance. This problem becomes very serious under high loads.To alleviate this problem, in this paper, we present ascheduling policy called Faithful Scheduling (FF), which dramatically reduces context-switches as well as lock-holder thread preemptions. We implemented FF on a 24-core Dell PowerEdgeR905 server running OpenSolaris.2009.06 and evaluated it using 22 programs including the TATP database application, SPECjbb2005, programs from PARSEC, SPEC OMP, and some microbenchmarks. The experimental results show that FF policy achieves high performance for both lightly and heavily loaded systems. Moreover it does not require any changes to the application source code or the OS kernel.
Kishore Kumar Pusukuri, Rajiv Gupta, and Laxmi N. Bhuyan
Efficient contention management is the key to achieving scalable performance for multithreaded applications running on multicore systems. However, contention management policies provided by modern operating systems increase context-switches and lead to performance degradation for multithreaded applications under high loads. Moreover, this problem is exacerbated by the interaction between contention management policies and OS scheduling polices. Time Share(TS) is the default scheduling policy in a modern OS such as OpenSolaris and with TS policy, priorities of threads change very frequently for balancing load and providing fairness inscheduling. Due to the frequent ping-ponging of priorities, threads of an application are often preempted by the threads of the same application. This increases the frequency of involuntary context-switches as wells as lock-holder thread preemptions and leads to poor performance. This problem becomes very serious under high loads.To alleviate this problem, in this paper, we present ascheduling policy called Faithful Scheduling (FF), which dramatically reduces context-switches as well as lock-holder thread preemptions. We implemented FF on a 24-core Dell PowerEdgeR905 server running OpenSolaris.2009.06 and evaluated it using 22 programs including the TATP database application, SPECjbb2005, programs from PARSEC, SPEC OMP, and some microbenchmarks. The experimental results show that FF policy achieves high performance for both lightly and heavily loaded systems. Moreover it does not require any changes to the application source code or the OS kernel.
A Unified Scheduler for Recursive and Task Dataflow Parallelism
PACT Conference 11 Octubre de 2011, 17:00 Spanish Time, Galveston ISland TX,USA, Hotel Galvez, Music Hall.
Hans Vandierendonck
Hans Vandierendonck
Task dataflow languages simplify the specification of parallel programs by dynamically detecting and enforcing dependencies between tasks. These languages are, however, often restricted to a single level of parallelism. This language design is reflected in the runtime system, where a master thread explicitly generates a task graph and worker threads execute ready tasks and wake-up their dependents. Such an approach is incompatible with state-of-the-art schedulers such as the Cilk scheduler, that minimize the creation of idle tasks (work-first principle) and place all task creation and scheduling off the critical path. This paper proposes an extension to the Cilk scheduler in order to reconcile task dependencies with the work-first principle. We discuss the impact of task dependencies on the properties of the Cilk scheduler. Furthermore, we propose a low-over head ticket-based technique for dependency tracking and enforcement at the object level. Our scheduler also supports renaming of objects in order to increase task-level parallelism. Renaming is implemented using versioned objects, a new type of hyperobject. Experimental evaluation shows that the unified scheduler is as efficient as the Cilk scheduler when tasks have no dependencies.Moreover, the unified scheduler is more efficient than SMPSS, a particular implementation of a task dataflow language.
Suscribirse a:
Entradas (Atom)
