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pro vyhledávání: '"Dipti Shankar"'
An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep learning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1923ae10e21213895d608dac797e1cc6
https://doi.org/10.7551/mitpress/11451.001.0001
https://doi.org/10.7551/mitpress/11451.001.0001
Publikováno v:
Current Research Journal of Social Sciences & Humanities; 2023, Vol. 6 Issue 1, p122-131, 10p
Publikováno v:
SC
Byte-addressable persistent memory (PMEM) can be directly manipulated by Remote Direct Memory Access (RDMA) capable networks. However, existing studies to combine RDMA and PMEM can not deliver the desired performance due to their PMEM-oblivious commu
Byte-addressable persistent memory (PMEM) can be directly manipulated by Remote Direct Memory Access (RDMA) capable networks. However, existing studies to combine RDMA and PMEM can not deliver the desired performance due to their PMEM-oblivious commu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d97592819bc79e4a4a3bbdc3e2e77a4
Publikováno v:
Journal of Parallel and Distributed Computing. 120:237-250
MapReduce is the most popular parallel computing framework for big data processing which allows massive scalability across distributed computing environment. Advanced RDMA-based design of Hadoop MapReduce has been proposed that alleviates the perform
An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep learning.Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness
Publikováno v:
IISWC
With the emergence of modern multi-core CPU architectures that support data parallelism via vectorization, several storage systems have been employing SIMD-based techniques to optimize data-parallel operations on in-memory structures like hash-tables
Publikováno v:
HPDC
Distributed storage systems typically need data to be stored redundantly to guarantee data durability and reliability. While the conventional approach towards this objective is to store multiple replicas, today's unprecedented data growth rates encou
Publikováno v:
IEEE BigData
Efficient Big Data analytics on Cloud Computing systems is still full of challenges. One of the biggest hurdles is the unsatisfactory performance offered by underlying virtualized I/O devices such as networks. To address this issue, the modern cloud
Publikováno v:
The Journal of Supercomputing. 72:4573-4600
With the emergence of high-performance data analytics, the Hadoop platform is being increasingly used to process data stored on high-performance computing clusters. While there is immense scope for improving the performance of Hadoop MapReduce (inclu