Performance Characterization of In-Memory Data Analytics on a Modern Cloud Server

In last decade, data analytics have rapidly progressed from traditional disk-based processing to modern in-memory processing. However, little effort has been devoted at enhancing performance at micro-architecture level. This paper characterizes the performance of in-memory data analytics using Apache Spark framework. We use a single node NUMA machine and identify the bottlenecks hampering the scalability of workloads. We also quantify the inefficiencies at micro-architecture level for various data analysis workloads. Through empirical evaluation, we show that spark workloads do not scale linearly beyond twelve threads, due to work time inflation and thread level load imbalance. Further, at the micro-architecture level, we observe memory bound latency to be the major cause of work time inflation.Comment: Accepted to The 5th IEEE International Conference on Big Data and Cloud Computing (BDCloud 2015

Aplicació mòbil de productivitat en grup basada en el mètode pomodoro.

L'aplicació d'aquest projecte, TikTak Team, vol portar els beneficis de la Tècnica Pomodoro (tècnica per gestionar el temps de forma individual) a la dimensió del treball en grup i la gestió de tasques, oferint la possiblitat a grups de persones de sincronitzar els temps de treball i descans.TikTak Team, the app of this project, wants to bring the benefits of the Pomodoro Technique (a technique used to manage time in an individual way) to the dimension of teamwork and task management, making teams capable to synchronize the moments of work and rest

Introducing the Task-Aware Storage I/O (TASIO) Library

Task-based programming models are excellent tools to parallelize and seamlessly load balance an application workload. However, the integration of I/O intensive applications and task-based programming models is lacking. Typically, I/O operations stall the requesting thread until the data is serviced by the backing device. Because the core where the thread was running becomes idle, it should be possible to overlap the data query operation with either computation workloads or even more I/O operations. Nonetheless, overlapping I/O tasks with other tasks entails an extra degree of complexity currently not managed by programming models’ runtimes. In this work, we focus on integrating storage I/O into the tasking model by introducing the Task-Aware Storage I/O (TASIO) library. We test TASIO extensively with a custom benchmark for a number of configurations and conclude that it is able to achieve speedups up to 2x depending on the workload, although it might lead to slowdowns if not used with the right settings.This project is supported by the European Union's Horizon 2021 research and innovation programme under the grant agreement No 754304 (DEEP-EST), the Ministry of Economy of Spain through the Severo Ochoa Center of Excellence Program (SEV-2015-0493), by the Spanish Ministry of Science and Innovation (contract TIN2015-65316-P) and by the Generalitat de Catalunya (2017-SGR- 1481). Also, the authors would like to acknowledge that the test environment (Cobi) was ceded by Intel Corporation in the frame of the BSC - Intel collabo- ration.Peer ReviewedPostprint (author's final draft

Shared Memory Pipelined Parareal

For the parallel-in-time integration method Parareal, pipelining can be used to hide some of the cost of the serial correction step and improve its efficiency. The paper introduces an OpenMP implementation of pipelined Parareal and compares it to a standard MPI-based variant. Both versions yield almost identical runtimes, but, depending on the compiler, the OpenMP variant consumes about 7% less energy and has a significantly smaller memory footprint. However, its higher implementation complexity might make it difficult to use in legacy codes and in combination with spatial parallelisation

Aplicació mòbil de productivitat en grup basada en el mètode pomodoro.

L'aplicació d'aquest projecte, TikTak Team, vol portar els beneficis de la Tècnica Pomodoro (tècnica per gestionar el temps de forma individual) a la dimensió del treball en grup i la gestió de tasques, oferint la possiblitat a grups de persones de sincronitzar els temps de treball i descans.TikTak Team, the app of this project, wants to bring the benefits of the Pomodoro Technique (a technique used to manage time in an individual way) to the dimension of teamwork and task management, making teams capable to synchronize the moments of work and rest