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Browser-Level Parallelism and Interactive Rendering APIs for Scalable Computation-Intensive SaaS: Application to Brain Diffusion MRI.

Authors :
Benmerar, Tarik Zakaria
Megherbi, Thinhinane
Kachouane, Mouloud
Deriche, Rachid
Oulebsir-Boumghar, Fatima
Source :
IEEE Transactions on Services Computing; Jul/Aug2021, Vol. 14 Issue 4, p971-984, 14p
Publication Year :
2021

Abstract

Due to their heavy reliance on server infrastructure, the current computation-intensive SaaS suffer from scalability issues compared to the existing data-intensive commercial SaaS. Offloading certain computations to the client browser can resolve these scalability issues but the current Browser APIs are complex to use and integrate in a single software. We propose in this paper four high level APIs that harness existing browser-based paradigms and proven software architectures to reduce the complexity of parallel computing and device-agnostic interactive rendering in the web browser. To allow experimental results, we have developed a proof-of-concept browser-based and interactive diffusion MRI where we have particularly deployed a parallel Diffusion Tensor Estimation. Our platform provides us easy APIs achieving up to 4 times speedup in parallel computation and real-time interactive rendering performances across different Browsers and Devices in comparison to other existing solutions in the Diffusion MRI Community. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19391374
Volume :
14
Issue :
4
Database :
Complementary Index
Journal :
IEEE Transactions on Services Computing
Publication Type :
Academic Journal
Accession number :
153127630
Full Text :
https://doi.org/10.1109/TSC.2018.2847354