A Survey and Comparative Study of Hard and Soft Real-time Dynamic Resource Allocation Strategies for Multi/Many-core Systems

Multi-/many-core systems are envisioned to satisfy the ever-increasing performance requirements of complex applications in various domains such as embedded and high-performance computing. Such systems need to cater to increasingly dynamic workloads, requiring efficient dynamic resource allocation strategies to satisfy hard or soft real-time constraints. This article provides an extensive survey of hard and soft real-time dynamic resource allocation strategies proposed since the mid-1990s and highlights the emerging trends for multi-/many-core systems. The survey covers a taxonomy of the resource allocation strategies and considers their various optimization objectives, which have been used to provide comprehensive comparison. The strategies employ various principles, such as market and biological concepts, to perform the optimizations. The trend followed by the resource allocation strategies, open research challenges, and likely emerging research directions have also been provided

Prediction of Cellular Burden with Host--Circuit Models

Heterologous gene expression draws resources from host cells. These resources include vital components to sustain growth and replication, and the resulting cellular burden is a widely recognised bottleneck in the design of robust circuits. In this tutorial we discuss the use of computational models that integrate gene circuits and the physiology of host cells. Through various use cases, we illustrate the power of host-circuit models to predict the impact of design parameters on both burden and circuit functionality. Our approach relies on a new generation of computational models for microbial growth that can flexibly accommodate resource bottlenecks encountered in gene circuit design. Adoption of this modelling paradigm can facilitate fast and robust design cycles in synthetic biology

Design Space Exploration and Resource Management of Multi/Many-Core Systems

The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends

What determines growth potential and juvenile quality of farmed fish species?

Enhanced production of high quality and healthy fry is a key target for a successful and competitive expansion of the aquaculture industry. Although large quantities of fish larvae are produced, survival rates are often low or highly variable and growth potential is in most cases not fully exploited, indicating significant gaps in our knowledge concerning optimal nutritional and culture conditions. Understanding the mechanisms that control early development and muscle growth are critical for the identification of time windows in development that introduce growth variation, and improve the viability and quality of juveniles. This literature review of the current state of knowledge aims to provide a framework for a better understanding of fish skeletal muscle ontogeny, and its impact on larval and juvenile quality as broadly defined. It focuses on fundamental biological knowledge relevant to larval phenotype and quality and, in particular, on the factors affecting the development of skeletal muscle. It also discusses the available methodologies to assess growth and larvae/juvenile quality, identifies gaps in knowledge and suggests future research directions. The focus is primarily on the major farmed non-salmonid fish species in Europe that include gilthead sea bream, European sea bass, turbot, Atlantic cod, Senegalese sole and Atlantic halibut

Is emissions trading a solution to climate change?- A study with the focus on the European Union Emissions Trading Scheme

Climate change affects us all through rising sea levels, environmental degradation and rising temperatures. The issue with climate change emerges from the fact that the discharge of carbon dioxide creates negative externalities, which causes the market to reach an inefficient allocation. The European Union has chosen to respond to the problem with a market-based policy and established an emissions trading scheme (ETS) to create a market for carbon dioxide. The market puts a price on the right to emit and therefore creates an incentive for companies to reduce their emissions. Whether this market has had any impact on the emissions of carbon dioxide and can therefore be a solution to climate change is the question being treated in my report. The question is addressed through a qualitative approach where environmental economic theory is compared with the reality of emissions trading. The progress towards emission reductions is determined based on current reports from leading organizations such as the European Environmental Agency. The market for carbon dioxide in the European Union has so far exhibited some proof of contributing to emission reductions, but has the at the same time encountered issues such as a loose cap put on the carbon dioxide emissions, which has led to an unstable price on the emission allowances. The excessive lobbying from companies for these allowances is also a problem with the marked-based policy. On the other hand, the EU ETS has in some periods successfully put a price on carbon dioxide and companies have responded to the policy. Based on the current report from the European Environmental Agency, small emission reductions will be reached through the EU ETS. But the target of an emission reduction of 8% relative to the base year 1990 to which the EU-15 has common committed to in the Kyoto Protocol, will probably not be reached. Based on my findings, the EU ETS in its current form is not the solution to climate change, however may together in a policy mix with other policies targeting individual behavior, technical change and clean energy be a part of the solution to climate change

BioScript: programming safe chemistry on laboratories-on-a-chip

This paper introduces BioScript, a domain-specific language (DSL) for programmable biochemistry which executes on emerging microfluidic platforms. The goal of this research is to provide a simple, intuitive, and type-safe DSL that is accessible to life science practitioners. The novel feature of the language is its syntax, which aims to optimize human readability; the technical contributions of the paper include the BioScript type system and relevant portions of its compiler. The type system ensures that certain types of errors, specific to biochemistry, do not occur, including the interaction of chemicals that may be unsafe. The compiler includes novel optimizations that place biochemical operations to execute concurrently on a spatial 2D array platform on the granularity of a control flow graph, as opposed to individual basic blocks. Results are obtained using both a cycle-accurate microfluidic simulator and a software interface to a real-world platform

Adaptive Knobs for Resource Efficient Computing

Performance demands of emerging domains such as artificial intelligence, machine learning and vision, Internet-of-things etc., continue to grow. Meeting such requirements on modern multi/many core systems with higher power densities, fixed power and energy budgets, and thermal constraints exacerbates the run-time management challenge. This leaves an open problem on extracting the required performance within the power and energy limits, while also ensuring thermal safety. Existing architectural solutions including asymmetric and heterogeneous cores and custom acceleration improve performance-per-watt in specific design time and static scenarios. However, satisfying applications’ performance requirements under dynamic and unknown workload scenarios subject to varying system dynamics of power, temperature and energy requires intelligent run-time management. Adaptive strategies are necessary for maximizing resource efficiency, considering i) diverse requirements and characteristics of concurrent applications, ii) dynamic workload variation, iii) core-level heterogeneity and iv) power, thermal and energy constraints. This dissertation proposes such adaptive techniques for efficient run-time resource management to maximize performance within fixed budgets under unknown and dynamic workload scenarios. Resource management strategies proposed in this dissertation comprehensively consider application and workload characteristics and variable effect of power actuation on performance for pro-active and appropriate allocation decisions. Specific contributions include i) run-time mapping approach to improve power budgets for higher throughput, ii) thermal aware performance boosting for efficient utilization of power budget and higher performance, iii) approximation as a run-time knob exploiting accuracy performance trade-offs for maximizing performance under power caps at minimal loss of accuracy and iv) co-ordinated approximation for heterogeneous systems through joint actuation of dynamic approximation and power knobs for performance guarantees with minimal power consumption. The approaches presented in this dissertation focus on adapting existing mapping techniques, performance boosting strategies, software and dynamic approximations to meet the performance requirements, simultaneously considering system constraints. The proposed strategies are compared against relevant state-of-the-art run-time management frameworks to qualitatively evaluate their efficacy