Buffer Trees : Utility And Applications For External Memory Data Processing

Cache memory is the fastest memory outside of the CPU, runs at 10-30 ns per access.

Memory segmentation is the division of a computer's primary memory information into sections. Segments are applied in object records of compiled programs when linked together into a program image and when the image is loaded into the memory. Segmentation sights a logical address as a collection of segments. Each segment has a name and length. With the addresses specifying both the segment name and the offset within the segment. Therefore the user specifies each address by two quantities: a segment name and an offset. When compared to the paging scheme, the user specifies a single address, which is partitioned by the hardware into a page number and an offset, all invisible to the programmer. Memory segmentation is more visible

If an acid is added to a substance then the pH level will drop because you are adding more acid (HCl) to the solute becomes more acidic. While adding a base to a substance will cause the pH level to rise because adding more base (NaOH) to the solute would make it more basic.

Since the invention of the first computer, engineers have been conceptualizing and implementing ways to optimize system performance. The last 25 years have seen a rapid evolution of many of these concepts, particularly cache memory, virtual memory, pipelining, and reduced set instruction computing (RISC). Individual each one of these concepts has helped to increase speed and efficiency thus enhancing overall system performance. Most systems today make use of many, if not all of these concepts. Arguments can be made to support the importance of any one of these concepts over one

What is memorable? A memory has a major component to marketing, it is a kind of product that gives someone a feeling that they are back in the beginning. Which is the feeling of nostalgia, what can be defined as a yearning to relive the past that can produce lingering emotions.

In computer organization and architecture, memory is the most important part of a computer. Every computer must have its own memory. Memory represents two stable or semi-stable states that are representing 1 and 0. It is capable of being written to at least once and read multiple times. In this lab, we will learn briefly on two parts of memory only, which are RAM and ROM. As we know that a memory can either be non-volatile (as seen in a read-only memory) or volatile (used in random access memory).

In the last section of the paper we discuss the performance aspects of I/O and the major rules of the operating system design that can make

In the field of computer information, there is a vast amount of information that is used for operations. This information must be stored somewhere in order to be used in the future, and for programs to use

Currently there are various types of file format emerged and it is used for preserve the digital information. The main problems of these files format are not preserved digitally. The products of digital information’s are produce in word processing, spread sheet, data base, formula, chat, multimedia, etc. Heterogeneous way the information are store in these files and it is required pacific software for access these files.

This paper describes about linear data structure i.e. linked list. Linked list is dynamic in nature means there is no need to know size of data in advance. It is linear collection of data elements which may or may not be stored at consecutive memory location. In linked list pointers are used for providing the linear order and each node is divided into parts for storing data and link part. This paper provides only overview that how linked list was created and what are its advantages over another data structure. It also defines how data is stored in linked list. What type of linked list can be? What basic operations can be performed on singly linked list? .And also tried to define applications of data structure.

overall reduction in the speed at which data in the memory device is accessed by the

Modern Data Centers always interested in the new technology for various web search analysis, web log, bigdata analysis, social networking, so in this tasks new technology implemented using parallel processing for large-scale database analysis, so the MapReduce is one of new technology to get amounts of data, perform massive computation, and extract critical knowledge out of big data for business intelligence, proper analysis of large scale of datasets, it requires accurate input output capacity from the large server systems to perform and analyze weblog data which is derived from two steps called mapping and reducing. Between these two steps, MapReduce requires a on important phase called shuffling phase which exchange the intermediate data. So at the point of data shuffling, by physically changing the location(moving) segments of intermediate data across disks, causes major I/O contention and generate the Input/Output problem such as large power consumption, high heat generation which accounts for a large portion of the operating cost of data centers in analyzing such big data. So in this synopsis we introduce the new virtual shuffling approach to enable well-organized data movement and reduce I/O problem for MapReduce shuffling, thereby reducing power consumption and conserving energy. Virtual shuffling is achieved through a combination of three techniques including a three-level segment table, near-demand merging, and dynamic and balanced merging subtrees. Our

The goal of this project is to come up with a scalable and efficient solution which can process heterogeneous data in the most simplified design possible in real time. Existing solutions are either not scalable or approach one kind of data and in

Abstract: Hashing is the convenient way to get access to an item based on the given key which is the requirement for efficient buffer cache management. Static hashing provides fastest access to an object at the cost of memory utilization, whereas sequential storage provides most efficient memory utilization at the cost of access time. To provide balance between two extremes dynamic hashing schemes are produced. The focus of this paper is to survey various dynamic hashing schemes with perspective to use it in database buffer cache management. It includes dynamic hashing techniques like Extendible hashing, Expandable Hashing, Spiral Storage, Linear

This is the introduction of multi-core processors and database systems. Database management system (DBMS) is a collection of programs that enables you to store, modify, and retrieve information from the database. There are many different types of DBMS, ranging from small systems that run on personal computers to huge systems that run on mainframes. Database management system is necessary transaction processing and query processing. Today, the parallel database system can run on multi-core platforms. Presented within an overview of how to design and implement multi-core machines have been affected by the database management system.