Adaptive performance modeling of data-intensive workloads for resource provisioning in virtualized environment
The processing of data-intensive workloads is a challenging and time-consuming task that
often requires massive infrastructure to ensure fast data analysis. The cloud platform is the …
often requires massive infrastructure to ensure fast data analysis. The cloud platform is the …
Energy-aware and machine learning-based resource provisioning of in-memory analytics on cloud
In this work, we propose a proactive online resource provisioning methodology that
addresses the challenge of resource provisioning for IMC workloads in heterogeneous …
addresses the challenge of resource provisioning for IMC workloads in heterogeneous …
A scalable, research oriented, generic, sensor data platform
Research interests spanning numerous domains increasingly rely upon computational
systems which can store and process a large volume of variable data that is stored at high …
systems which can store and process a large volume of variable data that is stored at high …
A comprehensive memory analysis of data intensive workloads on server class architecture
HM Makrani, H Sayadi, SMP Dinakarra… - Proceedings of the …, 2018 - dl.acm.org
The emergence of data analytics frameworks requires computational resources and memory
subsystems that can naturally scale to manage massive amounts of diverse data. Given the …
subsystems that can naturally scale to manage massive amounts of diverse data. Given the …
Main-memory requirements of big data applications on commodity server platform
The emergence of big data frameworks requires computational and memory resources that
can naturally scale to manage massive amounts of diverse data. It is currently unclear …
can naturally scale to manage massive amounts of diverse data. It is currently unclear …
EALI: Energy-aware layer-level scheduling for convolutional neural network inference services on GPUs
C Yao, W Liu, Z Liu, L Yan, S Hu, W Tang - Neurocomputing, 2022 - Elsevier
The success of convolutional neural networks (CNNs) has made low-latency inference
services on Graphic Processing Units (GPUs) a hot research topic. However, GPUs are …
services on Graphic Processing Units (GPUs) a hot research topic. However, GPUs are …
Compressive sensing on storage data: An effective solution to alleviate i/0 bottleneck in data-intensive workloads
The gap between computation speed and I/O access on modern computing systems
imposes processing limitations in data-intensive applications. Employing high-end memory …
imposes processing limitations in data-intensive applications. Employing high-end memory …
Optimal allocation of computation and communication in an IoT network
A Chopra, H Aydin, S Rafatirad… - ACM Transactions on …, 2018 - dl.acm.org
Internet of things (IoT) is being developed for a wide range of applications from home
automation and personal fitness to smart cities. With the extensive growth in adaptation of …
automation and personal fitness to smart cities. With the extensive growth in adaptation of …
Universal steganalysis using color correlation and feature fusion
Y Tu, S Gong - 2008 International Symposium on Information …, 2008 - ieeexplore.ieee.org
A new universal steganalysis algorithm using YUV color space conversion and feature
combination of DCT (discrete cosine transform) and DWT (discrete wavelet transform) …
combination of DCT (discrete cosine transform) and DWT (discrete wavelet transform) …
Energy-efficiency prediction of multithreaded workloads on heterogeneous composite cores architectures using machine learning techniques
H Sayadi - arXiv preprint arXiv:1808.01728, 2018 - arxiv.org
Heterogeneous architectures have emerged as a promising alternative for homogeneous
architectures to improve the energy-efficiency of computer systems. Composite Cores …
architectures to improve the energy-efficiency of computer systems. Composite Cores …