Manycore Partitioning for Big Data Processing: Does Core Affinity Matter?
نویسندگان
چکیده
In this study, we aim to investigate the impact of core affinity on big data processing and discuss the potential for manycore partitioning that decides the core affinity based on the characteristics of threads, some of which are I/O intensive, some are computation intensive.
منابع مشابه
Parallelizing Affinity Propagation using GPUs for Spatial Cluster Analysis over Big Geospatial Data
Geocomputation has been the foundation of Geoinformatics for knowledge discovery through spatial and temporal data mining and analytics. Traditionally, Geoinformatics software products were developed based on serial computer programs for desktop application. Constrained by the hardware infrastructure and software solutions, geocomputation may not be accomplishable to process and analyze data wi...
متن کاملFPGA Prototyping of Manycore Multinode Systems for Irregular Applications
Knowledge discovery applications are an emerging class of irregular applications that exploit graph-based data structures, present poor locality and analyze very big data sets that require multi-node systems for processing. Current commodity clusters, which exploit cachebased processors, usually perform poorly with these applications. To address their requirements, full-custom machines, like th...
متن کاملPartitioning and Task Transfer on NoC-based Many-Core Processors in the Avionics Domain
Networks-on-Chip (NoC) based many-core processors can not only increase system performance but also allow the integration of multiple functions on a single hardware platform. To consolidate functionality on many-core systems in safety-critical domains software partitioning is required to avoid the propagation of faults due to the use of shared resources. In this paper we propose extensions to w...
متن کاملHigh-Throughput Maps on Message-Passing Manycore Architectures: Partitioning versus Replication
The advent of manycore architectures raises new scalability challenges for concurrent applications. Implementing scalable data structures is one of them. Several manycore architectures provide hardware message passing as a means to efficiently exchange data between cores. In this paper, we study the implementation of high-throughput concurrent maps in message-passing manycores. Partitioning and...
متن کاملC-Bound: A Capacity and Concurrency Driven Analytical Model for Many-core Design
In this paper, we propose C-Bound, a data-driven analytical model, that incorporates both memory capacity and data access concurrency factors to optimize many-core design. C-Bound is characterized by combining the newly proposed latency model, concurrent average memory access time (CAMAT), with the well-known memory-bounded speedup model (Sun-Ni’s law) to facilitate computing tasks. Compared to...
متن کامل