scholarly journals Hardware software partitioning using directed acyclic data dependence graph with precedence

2021 ◽  
Author(s):  
Matthew Jin
Keyword(s):  
Block Matching ◽  
Communication Overhead ◽  
Data Dependency ◽  
Detection Techniques ◽  
Processing Elements ◽  
Partitioning Algorithm ◽  
Sobel Edge Detection ◽  
System Partitioning ◽  
System Designs ◽  
Partitioning Technique

n this these we present a system partitioning technique that employs C/C++ as input specification language for hardware/software co-design. The proposed algorithm is able to explore a number of partitioning solutions as compared to other partitioning research. This benefit is obtained by processing data dependency and precedence dependency simultaneously in a new representation called Directed Acyclic Data dependency Graph with Precedence (DADGP). DADGP is an extension of Directed Acyclic Graph (DAG) structure frequently used in the past for partitioning. The DADGP based partitioning algorithm minimizes communication overhead, overall system execution time as well as system cost in terms of hardware area. The algorithm analyzes the DADGP and tries to expose parallelism between processing elements and repeated tasks. The benefits of exposing parallelism with minimum inter PE communication overhead are shown in the experimental results. However, such benefits come with increase in cost due to additional hardware units and their interconnections. DADGP-based partitioning technique is also employed to implement block matching and SOBEL edge detection techniques. Overall, the proposed system partitioning algorithm is fast and powerful enough to handle complicated and large system designs.

scholarly journals Hardware software partitioning using directed acyclic data dependence graph with precedence

2021 ◽  
Author(s):  
Matthew Jin
Keyword(s):  
Block Matching ◽  
Communication Overhead ◽  
Data Dependency ◽  
Detection Techniques ◽  
Processing Elements ◽  
Partitioning Algorithm ◽  
Sobel Edge Detection ◽  
System Partitioning ◽  
System Designs ◽  
Partitioning Technique

n this these we present a system partitioning technique that employs C/C++ as input specification language for hardware/software co-design. The proposed algorithm is able to explore a number of partitioning solutions as compared to other partitioning research. This benefit is obtained by processing data dependency and precedence dependency simultaneously in a new representation called Directed Acyclic Data dependency Graph with Precedence (DADGP). DADGP is an extension of Directed Acyclic Graph (DAG) structure frequently used in the past for partitioning. The DADGP based partitioning algorithm minimizes communication overhead, overall system execution time as well as system cost in terms of hardware area. The algorithm analyzes the DADGP and tries to expose parallelism between processing elements and repeated tasks. The benefits of exposing parallelism with minimum inter PE communication overhead are shown in the experimental results. However, such benefits come with increase in cost due to additional hardware units and their interconnections. DADGP-based partitioning technique is also employed to implement block matching and SOBEL edge detection techniques. Overall, the proposed system partitioning algorithm is fast and powerful enough to handle complicated and large system designs.

Framework for GeoSpatial Query Processing by Integrating Cassandra With Hadoop

2019 ◽  
pp. 353-388
Author(s):  
S. Vasavi ◽  
Mallela Padma Priya ◽  
Anu A. Gokhale
Keyword(s):  
Response Time ◽  
Query Processing ◽  
Geospatial Data ◽  
Distributed Data ◽  
Nosql Databases ◽  
Storage And Retrieval ◽  
Query Response Time ◽  
Partitioning Algorithm ◽  
Hadoop Framework ◽  
Partitioning Technique

We are moving towards digitization and making all our devices, such as sensors and cameras, connected to internet, producing bigdata. This bigdata has variety of data and has paved the way to the emergence of NoSQL databases, like Cassandra, for achieving scalability and availability. Hadoop framework has been developed for storing and processing distributed data. In this chapter, the authors investigated the storage and retrieval of geospatial data by integrating Hadoop and Cassandra using prefix-based partitioning and Cassandra's default partitioning algorithm (i.e., Murmur3partitioner) techniques. Geohash value is generated, which acts as a partition key and also helps in effective search. Hence, the time taken for retrieving data is optimized. When users request spatial queries like finding nearest locations, searching in Cassandra database starts using both partitioning techniques. A comparison on query response time is made so as to verify which method is more effective. Results show the prefix-based partitioning technique is more efficient than Murmur3 partitioning technique.

Framework for GeoSpatial Query Processing by Integrating Cassandra With Hadoop

2018 ◽  
pp. 1-41
Author(s):  
S. Vasavi ◽  
Mallela Padma Priya ◽  
Anu A. Gokhale
Keyword(s):  
Response Time ◽  
Query Processing ◽  
Geospatial Data ◽  
Distributed Data ◽  
Nosql Databases ◽  
Storage And Retrieval ◽  
Query Response Time ◽  
Partitioning Algorithm ◽  
Hadoop Framework ◽  
Partitioning Technique

We are moving towards digitization and making all our devices, such as sensors and cameras, connected to internet, producing bigdata. This bigdata has variety of data and has paved the way to the emergence of NoSQL databases, like Cassandra, for achieving scalability and availability. Hadoop framework has been developed for storing and processing distributed data. In this chapter, the authors investigated the storage and retrieval of geospatial data by integrating Hadoop and Cassandra using prefix-based partitioning and Cassandra's default partitioning algorithm (i.e., Murmur3partitioner) techniques. Geohash value is generated, which acts as a partition key and also helps in effective search. Hence, the time taken for retrieving data is optimized. When users request spatial queries like finding nearest locations, searching in Cassandra database starts using both partitioning techniques. A comparison on query response time is made so as to verify which method is more effective. Results show the prefix-based partitioning technique is more efficient than Murmur3 partitioning technique.

scholarly journals Klasifikasi-PNN pada Citra Ikan Air Tawar dengan Sobel Edge Detection

KREA-TIF ◽  
2018 ◽  
Vol 6 (2) ◽  
pp. 66
Author(s):  
Puspa Eosina ◽  
Gibtha Fitri Laxmi ◽  
Fety Fatimah
Keyword(s):  
Neural Network ◽  
Edge Detection ◽  
Freshwater Fish ◽  
Probabilistic Neural Network ◽  
Data Display ◽  
Vector Data ◽  
Detection Techniques ◽  
Accuracy Result ◽  
Sobel Edge Detection ◽  
Shape Characteristics

<h1 align="center"><strong>Abstrak</strong></h1><p>Metode Sobel adalah salah satu teknik dalam edge detection (deteksi tepi) untuk mengekstraksi tepi dari citra ikan air tawar. Deteksi tepi adalah proses identifikasi keberadaan dan letak tepinya dengan diskontinuitas gambar yang tajam. Menggunakan data citra ikan sebanyak 200 gambar dari 10 jenis ikan air tawar, dilakukan pencarian model klasifikasi PNN sebagai model untuk identifikasi data ekstraksi citra ikan air tawar menggunakan metode Sobel.Ciri atau karakteristik yang digunakan dalam mengekstrak data ikan dalam penelitian ini adalah ciri bentuk, yang dapat dikenali melalui titik-titik yang membentuk tepi-tepi objek ikan. Kinerja algoritma Sobel dapat dinilai dari hasil tampilan data vektor yang menjadi ciri bentuk ikan, dimana estimasi nilai-nilai pixel dilakukan menggunakan operator konvolusi Sobel (convolution masks). Telah ditunjukkan bahwa algoritma ini bekerja dengan baik. Data hasil ekstraksi ini, untuk selanjutnya digunakan dalam mencari model klasifikasi PNN (Probabilistic Neural Network) untuk identifikasi ikan air tawar. Hasil perhitungan nilai akurasi dari model yang terbentuk, yaitu kurang dari 25%, menunjukkan model identifikasi yang diinginkan belum tercapai. Hasil ini dapat digunakan sebagai pembanding untuk membangun model identifikasi menggunakan metode klasifikasi yang lain pada penelitian selanjutnya.</p><p align="center"><strong><em>Abstract</em></strong><strong><em></em></strong></p><p><em>The Sobel method is one of the edge detection techniques to extract the edges of freshwater fish images. The Edge detection is the process of identifying the existence and position of the edge with a sharp discontinuity of images. Using 200 images of fish from 10 types of freshwater fish, the</em><em> </em><em>Probabilistic Neural Network</em><em> </em><em>(PNN) classification was performed on freshwater fish image extraction,  to obtain the model of identification.</em><em> </em><em>In this study, the Sobel method is used to extract images of the shape characteristics. The performance of the Sobel algorithm can be judged by the results of the vector data display which characterizes the shape of the fish, where the estimation of pixel values is performed using the convolution masks operator. It has been shown that this algorithm works well. The accuracy result of the obtain model, ie less than 25%, indicates the desired model of identification has not been achieved. This result can be used as a benchmark to construct an identification model using other classification methods in subsequent research.</em></p>

Hybrid Cooperative Energy Detection Techniques in Cognitive Radio Networks

2015 ◽  
pp. 1-37 ◽  
Author(s):  
Raza Umar ◽  
Fahham Mohammed ◽  
Mohamed Deriche ◽  
Asrar U. H. Sheikh
Keyword(s):  
Cognitive Radio ◽  
A Priori ◽  
Energy Detection ◽  
Communication Overhead ◽  
Test Statistic ◽  
Local Data ◽  
Secondary Users ◽  
Detection Techniques ◽  
Depth Analysis ◽  
Significant Performance

Cognitive Radio (CR) has emerged as a smart solution to spectrum bottleneck faced by current wireless services under which licensed spectrum is made available to unlicensed Secondary Users (SUs) through robust and efficient Spectrum Sensing (SS). Energy Detection (ED) is the dominantly used SS approach owing to its low computational complexity and ability to identify spectrum holes without requiring a priori knowledge of primary transmission characteristics. In this chapter, the authors present an in-depth analysis of the ED test statistic. Based on the double threshold ED, they analyze the performance of a Hybrid PSO-OR (Particle Swarm Optimization and OR) algorithm for cooperative SS. The sensing decision of “fuzzy” SUs is optimized using PSO and the final collective decision is made based on OR rule. The idea of using two thresholds is introduced to reduce the communication overhead in reporting local data/decision to the fusion center, which also offers reduced energy consumption. The Hybrid PSO-OR algorithm is shown to exhibit significant performance gain over the Hybrid EGC-OR algorithm.

A competitive algorithm for managing sharing in the distributed execution of functional programs

1997 ◽  
Vol 7 (4) ◽  
pp. 421-440
Author(s):  
GAD AHARONI ◽  
AMNON BARAK ◽  
AMIR RONEN
Keyword(s):  
A Priori ◽  
Computation Time ◽  
Cost Effective ◽  
Time Algorithm ◽  
Communication Overhead ◽  
Communication Costs ◽  
Processing Elements ◽  
On Line ◽  
Distributed Execution ◽  
Run Time

Execution of functional programs on distributed-memory multiprocessors gives rise to the problem of evaluating expressions that are shared between several Processing Elements (PEs). One of the main difficulties of solving this problem is that, for a given shared expression, it is not known in advance whether realizing the sharing is more cost effective than duplicating its evaluation. Realizing the sharing requires coordination between the sharing PEs to ensure that the shared expression is evaluated only once. This coordination involves relatively high communication costs, and is therefore only worthwhile when the shared expressions require much computation time to evaluate. In contrast, when the shared expression is not computation intensive, it is more cost effective to duplicate the evaluation, and thus avoid the communication overhead costs. This dilemma of deciding whether to duplicate the work or to realize the sharing stems from the unknown computation time that is required to evaluate a shared expression. This computation time is difficult to estimate due to unknown run-time evolution of loops and recursion that may be part of the expression. This paper presents an on-line (run-time) algorithm that decides which of the expressions that are shared between several PEs should be evaluated only once, and which expressions should be evaluated locally by each sharing PE. By applying competitive considerations, the algorithm manages to exploit sharing of computation-intensive expressions, while it duplicates the evaluation of expressions that require little time to compute. The algorithm accomplishes this goal even though it has no a priori knowledge of the amount of computation that is required to evaluate the shared expression. We show that this algorithm is competitive with a hypothetical optimal off-line algorithm, which does have such knowledge, and we prove that the algorithm is deadlock free. Furthermore, this algorithm does not require any programmer intervention, it has low overhead, and it is designed to run on a wide variety of distributed systems.

scholarly journals Identification of Virus in Microscopic Image Using Genetic Algorithm

2019 ◽  
Vol 8 (S2) ◽  
pp. 24-27
Author(s):  
N. Senthilkumaran ◽  
R. Preethi
Keyword(s):  
Genetic Algorithm ◽  
Image Segmentation ◽  
Edge Detection ◽  
Microscopic Image ◽  
Canny Edge Detection ◽  
Detection Techniques ◽  
Canny Edge ◽  
Sobel Edge Detection ◽  
The Many ◽  
Prewitt Edge Detection

In this paper describes a several techniques of effective edge detection by using image segmentation. The image segmentation provides various techniques to detect the edges on image. The paper mainly focused on edge detection using matlab parameters and solved the many problems. Edge detection techniques have a several type of techniques. We have taken microscopic image, which affects the human body by making diseases through viruses and bacteria’s. Now analyze only about the major techniques: a.) Roberts edge detection, b) sobel edge detection, c) prewitt edge detection, d) log (laplacian of gaussian) edge detection, e) genetic edge detection and f) canny edge detection. We have applied above five techniques which are used in edge detection and got a result on microscopic images. Hence, we scope this paper defines and compares the variety of techniques and demand assures the genetic algorithm provides a better performance on edge detection using microscopic image.

scholarly journals NIWAS: A non-interactive watermark authentication scheme for industrial field-programmable gate array designs

2018 ◽  
Vol 10 (6) ◽  
pp. 168781401877605 ◽  
Author(s):  
Jing Long ◽  
Dafang Zhang ◽  
Wei Liang ◽  
Zuoting Ning ◽  
Qingyong Zhang
Keyword(s):  
Intellectual Property ◽  
Field Programmable Gate Array ◽  
High Efficiency ◽  
Communication Overhead ◽  
Sensitive Information ◽  
Detection Techniques ◽  
Field Programmable ◽  
Gate Array ◽  
Location Obfuscation ◽  
Intellectual Property Infringement

Except the network attacks, the industrial networked devices in Internet of things are also threatened by intellectual property infringement. Watermarking technique is a prevalent way to avoid this threat. Previous work on authenticating a watermark in industrial intellectual properties easily discloses sensitive information of real embedded watermarks. In this case, the evidence of identifying the ownership of industrial intellectual property may be attacked by the illegal verifiers. Although several watermark detection techniques can address the disclosure of sensitive information in detection procedure, the efficiency of detection is relatively low. Besides, it may yield large communication overhead of multiple authentication rounds. Motivated by the needs of robustness and efficiency, this work proposed a zero-knowledge approach to authenticate ownership of field-programmable gate array intellectual property design in industrial environment, named NIWAS. The prover can convince the verifier that he knows a secret in the suspected intellectual property design via only one interaction. Real locations of watermarks are concealed through location obfuscation. With the received authentication package from the prover, the verifier cannot obtain other useful information about the watermarks. The experiments show that NIWAS achieves high efficiency and robustness of watermark detection.

AN EFFICIENT PROCESSOR ALLOCATION FOR NESTED PARALLEL LOOPS ON DISTRIBUTED MEMORY HYPERCUBES

1993 ◽  
Vol 03 (02) ◽  
pp. 179-187
Author(s):  
OSCAR PLATA ◽  
TOMAS F. PENA ◽  
FRANCISCO F. RIVERA ◽  
EMILIO L. ZAPATA
Keyword(s):  
Message Passing ◽  
Distributed Memory ◽  
Data Distribution ◽  
Communication Overhead ◽  
Processor Allocation ◽  
Realistic Approach ◽  
Parallel Loops ◽  
Partitioning Algorithm ◽  
Optimal Set ◽  
Nested Loop

We consider the static processor allocation problem for arbitrarily nested parallel loops on distributed memory, message-passing hypercubes. We present HYPAL (HYpercube Partitioning ALgorithm) as an efficient algorithm to solve this problem. HYPAL calculates an optimal set of partitions of the dimension of the hypercube, and assigns them to the set of iterations of the nested loop. Some considerations about the influence of the communication overhead in order to get a more realistic approach are considered. The main problem at this point is to obtain the communication pattern associated to the parallel program because it depends on scheduling and data distribution.

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