Search for dissertations about: "Memory Efficiency"

Showing result 1 - 5 of 187 swedish dissertations containing the words Memory Efficiency.

  2. 1. Bilingual memory : A lifespan approach

    Author : Sadegheh Moniri; Lars-Göran Nilsson; Judith Kroll; Stockholms universitet; []
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Bilingual model; children; elderly; memory; control; lexical selection; Psychology; Psykologi;

    Abstract : Bilingualism and its effect on individuals have been studied within different disciplines. Although the first psychological study of bilingualism was couducted by Cattell as early as 1887, only a few studies have exclusively investigated the effect of bilingualism on memory systems’ functioning. READ MORE

  4. 2. Techniques for Enhancing the Efficiency of Transactional Memory Systems

    Author : Shady Issa; Paolo Romano; Vladimir Vlassov; Mats Brorsson; Konstantin Busch; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Transactional Memory; Parallel Programming; Concurrency Control; Self-tuning; Energy Efficiency; Data Partitioning; Dynamic Frequency and Voltage Scaling DVFS ; Hardware Transactional Memory HTM ; Memória Transacional; Programação Paralela; Eficiência Energética; Mecanismos de Auto-configuração; Partição de Dados; Frequência Dinâmica e do Escalonamento de Voltagem DVFS ; Memória Transacional em Hardware HTM ; Transaktionellt Minne; Parallellprogrammering; Samtida Exekvering; Självjusterande; Energieffektivitet; Datapartitionering; Dynamisk Frekvens och Volttalsskalning; Informations- och kommunikationsteknik; Information and Communication Technology;

    Abstract : Transactional Memory (TM) is an emerging programming paradigm that drastically simplifies the development of concurrent applications by relieving programmers from a major source of complexity: how to ensure correct, yet efficient, synchronization of concurrent accesses to shared memory. Despite the large body of research devoted to this area, existing TM systems still suffer from severe limitations that hamper both their performance and energy efficiency. READ MORE

  5. 3. Reducing Memory Traffic with Approximate Compression

    Author : Albin Eldstål-Ahrens; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Memory Compression; Memory Systems; Compression; Computer Architecture; Lossy Compression; Approximate Computing;

    Abstract : Memory bandwidth is a critical resource in modern systems and has an increasing demand. The large number of on-chip cores and specialized accelerators improves the potential processing throughput but also calls for higher data rates. In addition, new emerging data-intensive applications further increase memory traffic. READ MORE

  6. 4. Towards Large-Capacity and Cost-Effective Main Memories

    Author : Dmitry Knyaginin; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Fairness; Energy Efficiency; Hybrid Main Memory; Performance; Design-Space Exploration; Parallel Memory Protocols; Large-Capacity Local Memory; Hardware-Based Hybrid Memory Management; Cost-Effectiveness;

    Abstract : Large, multi-terabyte main memories per processor socket are instrumental to address the continuously growing performance demands of domains like high-performance computing, databases, and big data. It is an important objective to design large-capacity main memories in a way that maximizes their cost-effectiveness and at the same time minimizes performance losses caused by cost-effective tradeoffs. READ MORE

  7. 5. Energy Efficiency in Machine Learning : Approaches to Sustainable Data Stream Mining

    Author : Eva García Martín; Håkan Grahn; Veselka Boeva; Emiliano Casalicchio; Jesse Read; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; machine learning; energy efficiency; data stream mining; green machine learning; edge computing; Computer Science; Datavetenskap;

    Abstract : Energy efficiency in machine learning explores how to build machine learning algorithms and models with low computational and power requirements. Although energy consumption is starting to gain interest in the field of machine learning, still the majority of solutions focus on obtaining the highest predictive accuracy, without a clear focus on sustainability. READ MORE