Softsku: Optimizing server architectures for microservice diversity@ scale

A Sriraman, A Dhanotia, TF Wenisch - Proceedings of the 46th …, 2019 - dl.acm.org
The variety and complexity of microservices in warehouse-scale data centers has grown
precipitously over the last few years to support a growing user base and an evolving product …

Semantic convolutional neural network model for safe business investment by using bert

M Heidari, S Rafatirad - 2020 Seventh International Conference …, 2020 - ieeexplore.ieee.org
The real estate market creates one of the significant business domains for investors, but a
wise investment in real estate is more important for low-income people who have just one …

Using transfer learning approach to implement convolutional neural network model to recommend airline tickets by using online reviews

M Heidari, S Rafatirad - 2020 15th International Workshop on …, 2020 - ieeexplore.ieee.org
Social Media provides an opportunity for people to share their idea about different aspects of
life. Traveling is one of the essential aspects of life. In this paper, we use Bidirectional …

Bidirectional transformer based on online text-based information to implement convolutional neural network model for secure business investment

M Heidari, S Rafatirad - 2020 IEEE International Symposium on …, 2020 - ieeexplore.ieee.org
Real estate investment decisions are critical for low-income people who have just one home
as their life-time investment option. So during the COVID-19 pandemic, unemployment …

Customized machine learning-based hardware-assisted malware detection in embedded devices

H Sayadi, HM Makrani, O Randive… - 2018 17th IEEE …, 2018 - ieeexplore.ieee.org
The emerging embedded systems, which account for a wide range of applications are often
highly resource-constrained challenging the conventional software-based methods …

Xppe: cross-platform performance estimation of hardware accelerators using machine learning

HM Makrani, H Sayadi, T Mohsenin… - Proceedings of the 24th …, 2019 - dl.acm.org
The increasing heterogeneity in the applications to be processed ceased ASICs to exist as
the most efficient processing platform. Hybrid processing platforms such as CPU+ FPGA are …

Utilizing cloud FPGAs towards the open neural network standard

D Danopoulos, C Kachris, D Soudris - Sustainable Computing: Informatics …, 2021 - Elsevier
Abstract Accurate and efficient Machine Learning algorithms are of vital importance to many
problems, especially on classification or clustering tasks but need a universal AI model …

Adaptive performance modeling of data-intensive workloads for resource provisioning in virtualized environment

HM Makrani, H Sayadi, N Nazari… - ACM Transactions on …, 2021 - dl.acm.org
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 …

Survey of memory management techniques for hpc and cloud computing

A Pupykina, G Agosta - IEEE Access, 2019 - ieeexplore.ieee.org
The emergence of new classes of HPC applications and usage models, such as real-time
HPC and cloud HPC, coupled with the increasingly heterogeneous nature of HPC …

Energy-aware and machine learning-based resource provisioning of in-memory analytics on cloud

HM Makrani, H Sayadi, D Motwani, H Wang… - Proceedings of the …, 2018 - dl.acm.org
In this work, we propose a proactive online resource provisioning methodology that
addresses the challenge of resource provisioning for IMC workloads in heterogeneous …