Application live-upgrading and error-recovery using code-data decoupling

When applications have critical bugs that present security vulnerabilities or may result in serious failures with potential massive business level impact, these applications have to be updated as fast as possible to minimize the harm of the bug. However, mission-critical or other user-facing applications may maintain critical internal state that has to be serialized and restored during the update process introducing signi1cant cost and delay. Instead of serializing the internal state we propose to implement applications in such a way that the application state is fully decoupled (e.g. in a different address space or shared memory segment) from the application logic. Such a decoupling allows for example that upgrades can happen without serialization of the data, even allowing side-by-side execution of the updated and the failing version of the application and thereby reducing application downtime during the update process. Furthermore, this decoupling also allows applications to recover easily from failures by recovering the previous data of the crashed application instance

X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs

Structured, or tabular, data is the most common format in data science. While deep learning models have proven formidable in learning from unstructured data such as images or speech, they are less accurate than simpler approaches when learning from tabular data. In contrast, modern tree-based Machine Learning (ML) models shine in extracting relevant information from structured data. An essential requirement in data science is to reduce model inference latency in cases where, for example, models are used in a closed loop with simulation to accelerate scientific discovery. However, the hardware acceleration community has mostly focused on deep neural networks and largely ignored other forms of machine learning. Previous work has described the use of an analog content addressable memory (CAM) component for efficiently mapping random forests. In this work, we focus on an overall analog-digital architecture implementing a novel increased precision analog CAM and a programmable network on chip allowing the inference of state-of-the-art tree-based ML models, such as XGBoost and CatBoost. Results evaluated in a single chip at 16nm technology show 119x lower latency at 9740x higher throughput compared with a state-of-the-art GPU, with a 19W peak power consumption

Improving Multicore System Performance through Data Compression

As applications become more and more complex, it is becoming extremely important to have sufficient compute power on the chip. Multicore and many-core systems have been introduced to address this problem. This chapter considers the multicore architecture that is a shared multiprocessor-based system, where a certain number of processors share the same memory address space. It uses a loop nest-based code parallelization strategy for executing array-based applications in this multicore architecture. The chapter focuses on array-based codes mainly because they appear very frequently in scientific computing domain and embedded image/video processing domain. It explores two different strategies for dividing the available processors between compression/decompression and application execution. In static strategy a fixed number of processors are allocated for performing compression/decompression activity, and this allocation is not changed during the course of execution. The main idea behind dynamic strategy is to eliminate the optimal processor selection problem of the static approach. © 2017 by John Wiley & Sons, Inc. All rights reserved

La música en Antequera a través de su Archivo Histórico Municipal. Catalogación, estudio y análisis

Esta tesis aborda un recorrido a lo largo de la historia de la colegiata de Antequera, centrando el estudio en la vida de su capilla musical y de sus fondos musicales, y estudiando la pervivencia de esta una vez suprimida la colegial. Tras un trabajo previo de encuadre histórico, económico y social de la ciudad, se estudia la fundación de las parroquias y conventos de la ciudad, así como de su colegiata a través de importantes fuentes documentales conservadas en el Archivo Histórico Municipal de Antequera. Se ha realizado un trabajo de inventario, catalogación y datación de los cantorales de canto llano, de donde se han extraído importantes conclusiones, como la procedencia de distintas parroquias de estos fondos, ha sido posible la datación de la práctica totalidad de cantorales, y se han descubierto importantes volúmenes. Hay que destacar un libro con obras compuestas en canto llano por el maestro Zameza, de las que se desconocía su existencia, y dos volúmenes (de 1868 y 1907) con obras tardías de canto llano. Estos libros, junto con otra abundante documentación ha demostrado la pervivencia de la capilla de música más allá de 1851, momento en que la colegial antequerana fue suprimida. Además, en la colección se conservan tres ejemplares de pasionarios que encierran en sus folios pasajes musicales escritos en sus márgenes, que tras un arduo estudio de recuperación y transcripción, han resultado ser pasajes polifónicos que sustituyen a sus mismos pasajes de canto llano. La documentación perteneciente a la propia colegial, nos da una valiosa información sobre la forma de interpretación de estas Pasiones, así como de la antigüedad de la misma. Por último, hay que destacar el hallazgo en estos fondos de una importante obra profana para piano solo de Joaquín Tadeo de Murguía, de la que tampoco se conocía su existencia. La tesis incluye varios anexos: esquema de la base de datos creada para el tratamiento de la información; fichas e índice de los libros de canto llano; transcripciones de pasajes polifónicos de las Pasiones, y del Liber Defunctorum; transcripción de la ceremonia de las Pasiones; y los intervinientes en las Pasiones y lamentaciones.Tesis Univ. Granada