A cross-stack, network-centric architectural design for next-generation datacenters

This thesis proposes a full-stack, cross-layer datacenter architecture based on in-network computing and near-memory processing paradigms. The proposed datacenter architecture is built atop two principles: (1) utilizing commodity, off-the-shelf hardware (i.e., processor, DRAM, and network devices) with minimal changes to their architecture, and (2) providing a standard interface to the programmers for using the novel hardware. More specifically, the proposed datacenter architecture enables a smart network adapter to collectively compress/decompress data exchange between distributed DNN training nodes and assist the operating system in performing aggressive processor power management. It also deploys specialized memory modules in the servers, capable of performing general-purpose computation and network connectivity. This thesis unlocks the potentials of hardware and operating system co-design in architecting application-transparent, near-data processing hardware for improving datacenter's performance, energy efficiency, and scalability. We evaluate the proposed datacenter architecture using a combination of full-system simulation, FPGA prototyping, and real-system experiments

On Developmental Formation of Patterns

The constantly increasing amount of resources available to engineers and scientists have allowed them to target larger problems whose size and complexity introduce new challenges: the time required to find the solution is longer, the solutions are more error prone, and the tests and repairs are more expensive. Self-organizing methods have recently been the promising pioneers in dependable robust design. Distributed self-organizing patterns can emerge to demonstrate the desired characteristics, either in form or functionality. At the same time, being inspired by the natural development of multicellular organisms, researchers have started using artificial development to improve features such as scalability or fault tolerance of the solution. However, the current solutions resulting from artificial development are either very small in size or very simple in architecture. The first part of this thesis introduces a method to emerge patterns that demonstrate given functionality whose architecture is not known in advance. The notable achievement is the innovative fitness function in the evolutionary algorithm used there, which increases the density of the solutions in the search space and more importantly, makes the often-extremely-rough search space smoother. The second and major part of this thesis studies formation of given large patterns from simpler initial patterns. This problem is solved in the framework of Cellular Automata. We push our methods to their limits by targeting large non-periodic patterns that have not been originally created by developmental methods. We use patterns for which the similar existing methods take a long time to find the solution, and their solutions are often large and seldom scalable. We suggest improvements to the existing methods to allow them find more efficient solutions, and also present two new methods to improve the results even further. In the end, we show that our suggested method also contributes to scalability. More specifically, our second suggested method decreases the growth rate of the solution to be slower than the growth rate of the problem size

Network insights on oxaliplatin anti-cancer mechanisms

Abstract Oxaliplatin has been a crucial component of combination therapies since admission into the clinic causing modest gains in survival across multiple malignancies. However, oxaliplatin functions in a non-targeted manner, posing a difficulty in ascertaining precise efficacy mechanisms. While previously thought to only affect DNA repair mechanisms, Platinum-protein adducts (Pt-Protein) far outnumber Pt-DNA adducts leaving a big part of oxaliplatin function unknown. Through preliminary network modeling of high throughput data, this article critically reviews the efficacy of oxaliplatin as well as proposes a better model for enhanced efficacy based on a network approach. In our study, not only oxaliplatin’s function in interrupting DNA-replication was confirmed, but also its role in initiating or intensifying tumorigenesis pathways was uncovered. From our data we present a novel picture of competing signaling networks that collectively provide a plausible explanation of chemotherapeutic resistance, cancer stem cell survival, as well as invasiveness and metastases. Here we highlight oxaliplatin signaling networks, their significance and the clinical implications of these interactions that verifies the importance of network modeling in rational drug design

Analysis of Customer Satisfaction and Loyalty Using BRImo

This research aims to analyze the customer satisfaction of BRImo app users. Descriptive qualitative research design describes systematically and accurately the facts and characteristics of customer satisfaction and loyalty of BRImo app users. The results showed that dominant customers were also satisfied and were most likely to tell positive things about the BRImo application. Bank BRI needs to evaluate customers who feel dissatisfied and disloyal

The unfinished agenda of communicable diseases among children and adolescents before the COVID-19 pandemic, 1990-2019: a systematic analysis of the Global Burden of Disease Study 2019

BACKGROUND: Communicable disease control has long been a focus of global health policy. There have been substantial reductions in the burden and mortality of communicable diseases among children younger than 5 years, but we know less about this burden in older children and adolescents, and it is unclear whether current programmes and policies remain aligned with targets for intervention. This knowledge is especially important for policy and programmes in the context of the COVID-19 pandemic. We aimed to use the Global Burden of Disease (GBD) Study 2019 to systematically characterise the burden of communicable diseases across childhood and adolescence. METHODS: In this systematic analysis of the GBD study from 1990 to 2019, all communicable diseases and their manifestations as modelled within GBD 2019 were included, categorised as 16 subgroups of common diseases or presentations. Data were reported for absolute count, prevalence, and incidence across measures of cause-specific mortality (deaths and years of life lost), disability (years lived with disability [YLDs]), and disease burden (disability-adjusted life-years [DALYs]) for children and adolescents aged 0-24 years. Data were reported across the Socio-demographic Index (SDI) and across time (1990-2019), and for 204 countries and territories. For HIV, we reported the mortality-to-incidence ratio (MIR) as a measure of health system performance. FINDINGS: In 2019, there were 3·0 million deaths and 30·0 million years of healthy life lost to disability (as measured by YLDs), corresponding to 288·4 million DALYs from communicable diseases among children and adolescents globally (57·3% of total communicable disease burden across all ages). Over time, there has been a shift in communicable disease burden from young children to older children and adolescents (largely driven by the considerable reductions in children younger than 5 years and slower progress elsewhere), although children younger than 5 years still accounted for most of the communicable disease burden in 2019. Disease burden and mortality were predominantly in low-SDI settings, with high and high-middle SDI settings also having an appreciable burden of communicable disease morbidity (4·0 million YLDs in 2019 alone). Three cause groups (enteric infections, lower-respiratory-tract infections, and malaria) accounted for 59·8% of the global communicable disease burden in children and adolescents, with tuberculosis and HIV both emerging as important causes during adolescence. HIV was the only cause for which disease burden increased over time, particularly in children and adolescents older than 5 years, and especially in females. Excess MIRs for HIV were observed for males aged 15-19 years in low-SDI settings. INTERPRETATION: Our analysis supports continued policy focus on enteric infections and lower-respiratory-tract infections, with orientation to children younger than 5 years in settings of low socioeconomic development. However, efforts should also be targeted to other conditions, particularly HIV, given its increased burden in older children and adolescents. Older children and adolescents also experience a large burden of communicable disease, further highlighting the need for efforts to extend beyond the first 5 years of life. Our analysis also identified substantial morbidity caused by communicable diseases affecting child and adolescent health across the world. FUNDING: The Australian National Health and Medical Research Council Centre for Research Excellence for Driving Investment in Global Adolescent Health and the Bill & Melinda Gates Foundation

pd-gem5: Simulation Infrastructure for Parallel/Distributed Computer Systems for Network-Driven Optimization

In developing and optimizing a parallel/distributed computer system, it is critical to study the impact of the com-plex interplay amongst processor, node, and network architectures on performance and power efficiency in de-tail. This necessitates a flexible, detailed, and open-source full-system simulation infrastructure, but our commu-nity lacks such an infrastructure. Responding to such a need, we present pd-gem5, a gem5-based infrastructure that can model and simulate a parallel/distributed computer system using multiple simulation hosts. We show that pd-gem5 running on 6 simulation hosts speeds up the simulation of a 24-node computer system up to 3.7? com-pared to simulating all 24 nodes in a single simulation host. As a use case of pd-gem5, we model a parallel/distributed computer system after enabling pd-gem5 with the Linux default ondemand governor. While running parallel/distributed workloads, we observe that a sudden in-crease in network activity often immediately leads to and/or is highly correlated with a high utilization of processors receiving the packets. However, the governor does not instantly increase the frequency of the processors. Such delayed responses often result in violations of service level agreements (SLAs), discouraging service providers from deploying an aggressive power management governor. To achieve both short response time and high energy-efficiency, we propose a network-driven power management governor and evaluate its efficacy compared with the default on-demand and performance governors

The Representation of the Arab Spring Narrative in English and Arabic News Media

Since its emergence in late December 2010, the Arab Spring narrative has sparked many controversies among researchers, commentators, analysts, and scholars from different disciplines around the world in terms of the causes and the reasons behind it and even its name: ‘Arab Spring’. This study explores the Arab Spring narrative from its emergence to its continuing dénouement in the English and Arabic mainstream news media from corpus-linguistic and critical discourse analytic perspectives. The Arab Spring bilingual corpus consists of two main sub-corpora, English and Arabic, compiled from LexisNexis and other news websites. Totalling 15,088 articles and 11,522,846 words, the English sub-corpus consists of 7,018 texts with total of 5,901,416 words, while the Arabic sub-corpus comprises 8,070 news texts and a total of 5,621,430 words. Taken from prominent news media outlets from Western, Arab and Islamic countries, and divided into two major text types (news and editorials and opinions) with date range coverage from 15 June 2010 until 31 August 2013, it allows us to diachronically and synchronically examine the discursive construction of the Arab Spring narrative. Combining quantitative and qualitative methods associated with Corpus Linguistics (CL) and Critical Discourse Analysis (CDA), the current study explores the key topics associated with the Arab Spring at both the linguistic as well as the semantic levels by means of frequency, keyword (KKW list function in my case), collocation list functions and concordance. Analysis also identifies the main news actors and news values. Actors and events are represented, negatively and positively by means of lexical choice, and the different presentation strategies indicate that many of the Arab Spring news stories are politically, socially, and ideologically polarized. The contrasting themes/concepts within the resulting semantic categories (by means of pairs of items with positive/negative connotations) are also prevalent. For example, at the lexical level the following contrasting pairs are revealed: democracy/dictatorship; religious, sectarian/secular; peace/ violence; government/regime; allies/enemy; corruption/ reform, opposition/ support. Similarly, at the grammatical level items, such as pro/anti, is/non- and not, also indicate the contrastive as well as the polarizing nature of the Arab Spring narrative