Parallel Computing Architectures and APIs: IoT Big Data Stream
Processing commences from the point high-performance uniprocessors
were becoming increasingly complex, expensive, and power-hungry. A
basic trade-off exists between the use of one or a small number of
such complex processors, at one extreme, and a moderate to very
large number of simpler processors, at the other. When combined
with a high-bandwidth, interprocessor communication facility leads
to significant simplification of the design process. However, two
major roadblocks prevent the widespread adoption of such moderately
to massively parallel architectures: the interprocessor
communication bottleneck, and the difficulty and high cost of
algorithm/software development. One of the most important reasons
for studying parallel computing architectures is to learn how to
extract the best performance from parallel systems. Specifically,
you must understand its architectures so that you will be able to
exploit those architectures during programming via the standardized
APIs. This book would be useful for analysts, designers and
developers of high-throughput computing systems essential for big
data stream processing emanating from IoT-driven cyber-physical
systems (CPS). This pragmatic book: Devolves uniprocessors in terms
of a ladder of abstractions to ascertain (say) performance
characteristics at a particular level of abstraction Explains
limitations of uniprocessor high performance because of Moore's Law
Introduces basics of processors, networks and distributed systems
Explains characteristics of parallel systems, parallel computing
models and parallel algorithms Explains the three primary
categorical representatives of parallel computing architectures,
namely, shared memory, message passing and stream processing
Introduces the three primary categorical representatives of
parallel programming APIs, namely, OpenMP, MPI and CUDA Provides an
overview of Internet of Things (IoT), wireless sensor networks
(WSN), sensor data processing, Big Data and stream processing
Provides introduction to 5G communications, Edge and Fog computing
Parallel Computing Architectures and APIs: IoT Big Data Stream
Processing discusses stream processing that enables the gathering,
processing and analysis of high-volume, heterogeneous, continuous
Internet of Things (IoT) big data streams, to extract insights and
actionable results in real time. Application domains requiring data
stream management include military, homeland security, sensor
networks, financial applications, network management, web site
performance tracking, real-time credit card fraud detection, etc.
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