With computing systems undergone a fundamen- tal transformation from single-processor devices at the turn of the century to the ubiquitous and networked devices and the warehouse-scale computing via the cloud, the par...
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With computing systems undergone a fundamen- tal transformation from single-processor devices at the turn of the century to the ubiquitous and networked devices and the warehouse-scale computing via the cloud, the parallelism has become ubiquitous at many levels. At micro level, par- allelisms are being explored from the underlying circuits, to pipelining and instruction level parallelism on multi-cores or many cores on a chip as well as in a machine. From macro level, parallelisms are being promoted from multiple ma- chines on a rack, many racks in a data center, to the glob- ally shared infrastructure of the Internet. With the push of big data, we are entering a new era of parallel computing driven by novel and ground breaking research innovation on elas- tic parallelism and scalability. In this paper, we will give an overview of computing infrastructure for big data processing, focusing on architectural, storage and networking challenges of supporting big data paper. We will briefly discuss emerging computing infrastructure and technologies that are promising for improving data parallelism, task parallelism and encour- aging vertical and horizontal computation parallelism.
This paper advocates for the use of Intel SGX capable chips to deliver a secure and scalable architecture for Big Data processing in the cloud. The paper provides a novel Key-Value store service designed to use these ...
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ISBN:
(纸本)9781538680001
This paper advocates for the use of Intel SGX capable chips to deliver a secure and scalable architecture for Big Data processing in the cloud. The paper provides a novel Key-Value store service designed to use these new security capabilities as well as delivering a flexible mechanism to store hot, cold, and warm data using data replication, network coding, and hybrid mechanisms. We also describe various representative data streams from smart city sensors and applications gathered in Brazil used to tailor and guide our system design.
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