A new golden age for computer architecture

Hennessy, John L.; Patterson, David A.

doi:10.1145/3282307

Cited by 573 publications

(362 citation statements)

References 14 publications

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“…Benchmarking any product, including desktop computers, servers, data center architectures and mobile devices, always has its biases, fallacies and pitfalls [96], partly because it is hard to classify and match real-life scenarios. This can mislead architects to identify the wrong bottlenecks and make improper trade-offs [97].…”

Section: Discussion and Further Researchmentioning

confidence: 99%

Hadoop Oriented Smart Cities Architecture

Dıaconıța

Bologa

2018

Sensors

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A smart city implies a consistent use of technology for the benefit of the community. As the city develops over time, components and subsystems such as smart grids, smart water management, smart traffic and transportation systems, smart waste management systems, smart security systems, or e-governance are added. These components ingest and generate a multitude of structured, semi-structured or unstructured data that may be processed using a variety of algorithms in batches, micro batches or in real-time. The ICT architecture must be able to handle the increased storage and processing needs. When vertical scaling is no longer a viable solution, Hadoop can offer efficient linear horizontal scaling, solving storage, processing, and data analyses problems in many ways. This enables architects and developers to choose a stack according to their needs and skill-levels. In this paper, we propose a Hadoop-based architectural stack that can provide the ICT backbone for efficiently managing a smart city. On the one hand, Hadoop, together with Spark and the plethora of NoSQL databases and accompanying Apache projects, is a mature ecosystem. This is one of the reasons why it is an attractive option for a Smart City architecture. On the other hand, it is also very dynamic; things can change very quickly, and many new frameworks, products and options continue to emerge as others decline. To construct an optimized, modern architecture, we discuss and compare various products and engines based on a process that takes into consideration how the products perform and scale, as well as the reusability of the code, innovations, features, and support and interest in online communities.

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Section: Discussion and Further Researchmentioning

confidence: 99%

Hadoop Oriented Smart Cities Architecture

Dıaconıța

Bologa

2018

Sensors

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“…As presented above, detector data rates have increased by roughly 100-fold over the last 13 years, while the data throughput of CPU-based computing systems has improved much more slowly (Thompson, 2017;Thompson & Spanuth, 2018;Patterson, 2018;Hennessy & Patterson, 2019). State-ofthe art server systems are already saturating with data.…”

Section: Hardware Software Automation and The Need For Standardsmentioning

confidence: 99%

Gold Standard for macromolecular crystallography diffraction data

Bernstein

Förster²,

Bhowmick

et al. 2020

Int Union Crystallogr J

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Macromolecular crystallography (MX) is the dominant means of determining the three-dimensional structures of biological macromolecules. Over the last few decades, most MX data have been collected at synchrotron beamlines using a large number of different detectors produced by various manufacturers and taking advantage of various protocols and goniometries. These data came in their own formats: sometimes proprietary, sometimes open. The associated metadata rarely reached the degree of completeness required for data management according to Findability, Accessibility, Interoperability and Reusability (FAIR) principles. Efforts to reuse old data by other investigators or even by the original investigators some time later were often frustrated. In the culmination of an effort dating back more than two decades, a large portion of the research community concerned with high data-rate macromolecular crystallography (HDRMX) has now agreed to an updated specification of data and metadata for diffraction images produced at synchrotron light sources and X-ray free-electron lasers (XFELs). This `Gold Standard' will facilitate the processing of data sets independent of the facility at which they were collected and enable data archiving according to FAIR principles, with a particular focus on interoperability and reusability. This agreed standard builds on the NeXus/HDF5 NXmx application definition and the International Union of Crystallography (IUCr) imgCIF/CBF dictionary, and it is compatible with major data-processing programs and pipelines. Just as with the IUCr CBF/imgCIF standard from which it arose and to which it is tied, the NeXus/HDF5 NXmx Gold Standard application definition is intended to be applicable to all detectors used for crystallography, and all hardware and software developers in the field are encouraged to adopt and contribute to the standard.

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“…This section presents an overview of the system that includes the proposed HDES architecture, design, and heuristic applications that will be implemented and run in the system. HDES architectural design is based on computer architecture principles or embedded system principles [12]. We propose HDES working as a cluster that includes -heterogeneous embedded machines (HEMs).…”

Section: System Design Overviewmentioning

confidence: 99%

A Heuristic Approach for Scheduling in Heterogeneous Distributed Embedded Systems

Prongnuch¹,

Sitjongsataporn²,

Wiangtong³

2020

IJIES

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This paper presents a heuristic approach for workflow scheduling in heterogeneous distributed embedded system (HDES). A genetic algorithm (GA) and ant colony optimization (ACO) modified with the greedy algorithm introduced to the system contains multiple heterogeneous embedded machines (HEMs) working as a cluster. Users can remotely access and utilize their computational power. The communications on different types of buses are taken into account to find an optimal solution. New meta-heuristic information based on forwarding dependency is proposed to build probability for ACO to generate task priorities. Besides, a greedy algorithm for machine allocation is incorporated to complete task scheduling. Experiments based on random task graphs running in the HEM cluster demonstrate the effectiveness of the modified greedy ant colony optimization algorithm which outperforms the others by 33% more result quality.

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A new golden age for computer architecture

Abstract: Innovations like domain-specific hardware, enhanced security, open instruction sets, and agile chip development will lead the way.

Cited by 573 publications

References 14 publications

Hadoop Oriented Smart Cities Architecture

Hadoop Oriented Smart Cities Architecture

Gold Standard for macromolecular crystallography diffraction data

A Heuristic Approach for Scheduling in Heterogeneous Distributed Embedded Systems

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