Wyniki wyszukiwania - Biblioteka Nauki

1

A scalability Study of Columbia using the NAS Parallel Benchmarks

100%

Saini S. , Chang J. , Hood R. , Jin H.

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tom Vol. spec. issue

33-45

EN

The Columbia system at the NASA Advanced Supercomputing (NAS) facility is a cluster of 20 SGI Altix nodes, each with 512 Itanium 2 processors and 1 terabyte (TB) of shared-access memory. Four of the nodes are organized as a 2048-processor capabilitycomputing platform connected by two low-latency interconnects – NUMALink4 (NL4) and InfiniBand (IB). To evaluate the scalability of Columbia with respect to both increased processor counts and increased problem sizes, we used seven of the NAS Parallel Benchmarks and all three of the NAS multi-zone benchmarks. For NPB we ran three Classes B, C, and D of benchmarks. To measure the impact of some architectural features, we compared Columbia results with results obtained on a Cray Opteron Cluster consisting of 64 nodes, each with 2 AMD Opteron processors and 2 gigabytes (GB) of memory, connected with Myrinet 2000. In these experiments, we measured performance degradation due to contention for the memory buses on the SGI Altix BX2 nodes. We also observed the effectiveness of SGI’s NL4 interconnect over Myrinet. Finally, we saw that computations spanning multiple BX2 nodes connected with NL4 performed well. Some computations did almost as well when the IB interconnects was used.

2

Towards an Object-Oriented Programming Language for Physarum Polycephalum Computing : A Petri Net Model Approach

88%

Schumann A. , Pancerz K.

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2014

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tom Vol. 133, nr 2/3

271--285

EN

Our research is focused on creation of a new object-oriented programming language for Physarum polycephalum computing. Physarum polycephalum is a one-cell organism that can be used for developing a biological architecture of different abstract devices, among others, the digital ones. In the paper, we use an abstract graphical language in the form of Petri nets to describe the Physarum polycephalum behavior. Petri nets are a good formalism to assist designers and support hardware design tools, especially in developing concurrent systems. At the beginning stage considered in this paper, we show how to build Petri net models, and next implement them as Physarum polycephalum machines, of basic logic gates AND, OR, NOT, and simple combinational circuits on the example of the 1-to-2 demultiplexer.

3

Rough Sets Based LEM2 Rules Generation Supported by FPGA

88%

Kopczyński M. , Grześ T. , Stepaniuk J.

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tom Vol. 148, nr 1/2

107--122

EN

In this paper we propose a combination of capabilities of the FPGA based device and PC computer for rough sets based data processing resulting in generating decision rules. Presented architecture has been tested on the exemplary datasets. Obtained results confirm the significant acceleration of the computation time using hardware supporting rough set operations in comparison to software implementation.

4

Insights into neural architectures for learning numerical concepts from simple visual data

75%

Śluzek A.

Annals of Computer Science and Information Systems

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2022

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tom Vol. 30

205--209

EN

The paper reports some results on neural architectures for learning numerical concepts from visual data. We use datasets of small images with single-pixel dots (one to six per image) to learn the abstraction of small integers, and other numerical concepts (e.g. even versus odd numbers). Both fully-connected and convolutional architectures are investigated. The obtained results indicate that two categories of numerical properties apparently exist (in the context of discussed problems). In the first category, the properties can be learned without acquiring the counting skills, e.g. the notion of small, medium and large numbers. In the second category, explicit counting is embedded into the architecture so that the concepts are learned from numbers rather than directly from visual data. In general, we find that CNN architectures (if properly crafted) are more efficient in the discussed problems and (additionally) come with more plausible explainability.

5

Momik 8b - pierwszy polski minikomputer

63%

Komorowski W.

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2018

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tom Nr 7

129--141

PL

Przedstawiono różnicę między obecnym a oryginalnym, pochodzącym z lat 60. XX w., znaczeniem terminu „minikomputer”. Pierwszym polskim minikomputerem był 8-bitowy Momik 8b, zbudowany w 1973 r. Opisano szczegółowo jego listę rozkazów i system przerwań, a dodatkowo całą architekturę zdefiniowano w zapisie formalnym ISP.

EN

The difference between nowadays and original (emerged in 60’) meaning of the term minicomputer is pointed out. The full explanation of instruction set and interrupt system of Momik 8b is given. Additionally, the formal description of architecture in ISP notation is presented. Momik 8b was the first polish minicomputer and it was constructed in 1973.

6

Model sprzętowo-programistycznej platformy do testowania i uruchamiania wirtualnych systemów mikroprocesorowych

63%

Pucher K. , Namiota J.

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2009

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tom Vol. 50, nr 10

54-57

PL

W artykule przedstawiono model sprzętowo-programistycznej platformy pozwalającej na uruchamianie i testowanie systemów mikroprocesorowych, zaprojektowanych i zaimplementowanych za pomocą języków opisu sprzętu HDL. Zaprezentowana została idea pozwalająca na czytelne przedstawienie problematyki związanej z projektowaniem układów cyfrowych w tym głównie mikroprocesorowych, gdzie zwrócono szczególną uwagę na ukazanie wątków związanych z implementacją rozwiązań architektonicznych komputerów. Artykuł zawiera również odniesienie do fizycznej realizacji zaproponowanego modelu.

EN

This paper presents the model of a combined hardware and software platform that makes it possible to start-up and test microprocessor systems, already designed and implemented with use of Hardware Description Languages (HDL). It describes the idea to present problems associated with designing of digital circuits (in particular micro-porcessor ones) in a clear and comprehensible manner, where speciai attention is paid to presentation of aspects related to implementation of arcitectural solutions attributable to convetional computers. The study also contains references to tangible implementation of the proposed model within real projects.

7

One-shot federated learning with self-adversarial data

51%

Danilenka A. , Bogacka K. , Wasielewska-Michniewska K.

Annals of Computer Science and Information Systems

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2023

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tom Vol. 35

919--924

EN

Federated learning (FL) is a decentralized approach that aims at training a global model with the help of multiple devices, without collecting or revealing individual clients' data. The training of a federated model is conducted in communication rounds. Still, in certain scenarios, numerous communication rounds are impossible to perform. In such cases, a one-shot FL is utilized, where the number of communication rounds is limited to one. In this article, the idea of one-shot FL is enhanced with the usage of adversarial data, exploring and illustrating the possibilities to improve the performance of resulting global models, including scenarios with non-IID data, for image classification datasets: MNIST and CIFAR-10.

8

Concept of instruction set driven designing of CPU

51%

Pawłowski M. , Skorupski A. , Szymański Z. , Gracki K.

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tom Vol. 56, nr 10

95-97

EN

The paper presents idea of processors design with a preset instruction list. Each instruction is implemented as a functional logic block, attached to a common bus. Each of these blocks contains execution and control elements necessary to instruction execution. The processor is a combination of several dozen of such blocks. Only one is active after the recognition of the instruction code. The individual command blocks are described in VHDL and whole processor can be built in the FPGA.

PL

W artykule przedstawiono koncepcję projektowania procesorów za pomocą listy rozkazów. Każdy z rozkazów stanowi w pełni funkcjonalny blok logiczny, dołączony do wspólnych magistral i zawierający elementy wykonawcze i sterujące, które są niezbędne do jego wykonania. Procesor jest połączeniem kilkudziesięciu takich bloków, z których tylko jeden podejmuje działanie po rozpoznaniu swojego kodu rozkazu. Procesor jest realizowany w układzie FPGA, dlatego opis poszczególnych bloków rozkazowych jest projektowany w języku VHDL.

9

Short-term air pollution forecasting based on environmental factors and deep learning models

51%

Arsov M. , Zdravevski E. , Lameski P. , Corizzo R. , Koteli N. , Mitreski K. , Trajkovik V.

Annals of Computer Science and Information Systems

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2020

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tom Vol. 21

15--22

EN

The effects of air pollution on people, the environment, and the global economy are profound - and often under-recognized. Air pollution is becoming a global problem. Urban areas have dense populations and a high concentration of emission sources: vehicles, buildings, industrial activity, waste, and wastewater. Tackling air pollution is an immediate problem in developing countries, such as North Macedonia, especially in larger urban areas. This paper exploits Recurrent Neural Network (RNN) models with Long Short-Term Memory units to predict the level of PM10 particles in the near future (+3 hours), measured with sensors deployed in different locations in the city of Skopje. Historical air quality measurements data were used to train the models. In order to capture the relation of air pollution and seasonal changes in meteorological conditions, we introduced temperature and humidity data to improve the performance. The accuracy of the models is compared to PM10 concentration forecast using an Autoregressive Integrated Moving Average (ARIMA) model. The obtained results show that specific deep learning models consistently outperform the ARIMA model, particularly when combining meteorological and air pollution historical data. The benefit of the proposed models for reliable predictions of only 0.01 MSE could facilitate preemptive actions to reduce air pollution, such as temporarily shutting main polluters, or issuing warnings so the citizens can go to a safer environment and minimize exposure.

10

Reinforcement learning for on-line sequence transformation

51%

Rypeść G. , Lepak Ł. , Wawrzyński P.

Annals of Computer Science and Information Systems

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2022

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tom Vol. 30

133--139

EN

In simultaneous machine translation (SMT), an output sequence should be produced as soon as possible, without reading the whole input sequence. This requirement creates a trade-off between translation delay and quality because less context may be known during translation. In most SMT methods, this trade-off is controlled with parameters whose values need to be tuned. In this paper, we introduce an SMT system that learns with reinforcement and is able to find the optimal delay in training. We conduct experiments on Tatoeba and IWSLT2014 datasets against state-of-the-art translation architectures. Our method achieves comparable results on the former dataset, with better results on long sentences and worse but comparable results on the latter dataset.

11

Automatic detection of potential customers by opinion mining and intelligent agents

51%

Moreno R. , Fernandez-Isabel A. , Martín De Diego I. , Moguerza J. M. , Lancho C. , Cuesta Santa Teresa M.

Annals of Computer Science and Information Systems

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2022

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tom Vol. 30

93--101

EN

Nowadays, customer acquisition is an open issue that has a special interest in all companies over the world. Very different marketing campaigns using psychological methodologies are designed to address this issue. However, once a campaign is launched, it is highly complicated to detect which sets of customers are most likely to purchase an offered product. This fact is a key objective since it allows companies to focus their efforts on specific clients and discard others. Several selection techniques have been implemented but most of them are usually very demanding in terms of time and human resources for the companies. Artificial Intelligence techniques appear to help simplifying the process. Thus, companies have started to use Machine Learning (ML) models trained to efficiently detect those clients with certain proneness to purchase. In this sense, this paper presents a novel purchase propensity detection ML system based on the Sentiment Analysis techniques able to consider the customer comments regarding the offered products. The tourist domain has been selected for the case study, where the obtained product was successfully embedded in an initial prototype.