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Improving CPU-GPU System Performance Through Dynamic Management of LLC and NoC
, M.Sc. Thesis Sharif University of Technology ; Sarbazi Azad, Hamid (Supervisor)
Abstract
CPU-GPU Heterogeneous System Architectures (HSA) play an important role in today's computing systems. Because of fast-growing in technology and the necessity of high-performance computing, HSAs are widely used platforms. Integrating the multi-core Central Processing Unit (CPU) with many-core Graphics Processing Unit (GPU) on the same die combines the feature of both processors and providing better performance. The capacity of HSAs to provide high throughput of computing led to the widespread use of these systems. Besides the high performance of HSAs, we also face challenges. These challenges are caused by the use of two processors with different behaviors and requirements on the same die....
Single-Cell RNA-seq Dropout Imputation and Noise Reduction by Machine Learning
, M.Sc. Thesis Sharif University of Technology ; Soleymani Baghshah, Mahdih (Supervisor) ; Sharifi Zarchi, Ali (Supervisor) ; Goodarzi, Hani (Co-Supervisor)
Abstract
Single-cell RNA sequencing (scRNA-seq) technologies have empowered us to study gene expressions at the single-cell resolution. These technologies are developed based on barcoding of single cells and sequencing of transcriptome using next-generation sequencing technologies. Achieving this single-cell resolution is specially important when the target population is complex or heterogeneous, which is the case for most biological samples, including tissue samples and tumor biopsies.Single-cell technologies suffer from high amounts of noise and missing values, generally known as dropouts. This complexity can affect a number of key downstream analyses such as differential expression analysis,...
Agent-Based Optimization of Integrated Energy and Product Networks
, Ph.D. Dissertation Sharif University of Technology ; Bozorgmehry Boozarjomehry, Ramin (Supervisor) ; Pishvaie, Mahmoud Reza (Supervisor)
Abstract
The industrial paradigm shift toward intelligent and sustainable management stimulates policymakers to leverage artificial intelligence for the decentralized planning of chemical industries with energy networks. By doing so, this work firstly presents a simulation framework to investigate the rigorous transient behavior of integrated systems comprising natural gas and power transmission networks, along with a chemical plant whose feedstock is natural gas. This framework entails dynamic models for the gas transmission network and the SynGas plant, and a continuous-time AC-power flow formulation with dispatchable loads. It addresses the following key challenges: (i) analyzing energy and...