Unit 3 Quiz

RAM (Random Accesses Memory): RAM is used by CPU when a computer is running to store the information that it needs to be used very quickly but it does not store any information permanently.

These components can be combined in a large variety of configuration for very simple caching needs, like increasing the performance of the database access for a single application to the client, which very complex needs such as for grid

Short-term: First it selects a process that’s already in memory and ready to execute. Then it allocates the CPU to it.

atabase is a collection of data which describes the activities of one or more organizations in a well-defined structure and the structure of a database is specific and it has a purpose. Database Management System (DBMS) is used to control or organize the data in a database. Database Management System (DBMS) is also used for maintaining large collections of data. Distributed database can be defined as a collection of various databases which can be stored at different computer network locations. In this paper we discuss about Distributed Databases, their advantages and disadvantages.

Generally the CPU has fetch, decode, and execute operation. Most of today’s multi-core processors feature shared caches. In shared caches the caches are splitted into blocks and are used randomly by each core in a multi-core processor. Because of this there is severe delay experienced by each core and the processing speed is also reduced. This happens due to more time taken for read operation of memory and CPU. The problem faced by such architectures is cache contention. So far the time required for fetching is more when compared to the execution process. The fetching time must be reduced. Hence to address this problem, we have implemented a program that allows the usage of cache memory for each core of a processor at same time. In our concept, we execute all jobs of each

Therefore, the execution rate of all tasks is the same among all processors. Hence, the scheduling

CPU scheduling is the basis of multiprogrammed operating systems. By switching the CPU among processes, the operating system can make the computer more productive.

Another essential riddle in this area is the emulation of cache coherence. It should be noted that LactylMuset locates local-area networks. However, large-scale configurations might not be the panacea that systems engineers expected. Even though similar approaches improve the memory bus, we achieve this goal without harnessing the compelling unification of operating systems and context-free grammar.

A Spark cluster has two main components: master node and worker nodes. Each machine in the cluster is known as a node. There is a single master node and more than one worker nodes in a cluster. The master node allocates jobs to the worker nodes. A distributed file system e.g. HDFS, a cloud storage system e.g. S3 or a local file system is used for data storage. Spark can run on a single-node cluster setup having both master node and the worker node on the same machine. It also runs in a multi-node cluster setup. Spark applications run as independent sets of processes on a cluster.

For example if two users wish to use the same code, then instead of loading the code two times in to the table, one user can load it in to one table initially and later the other user who would like to use that code access the same memory location. This will help both the users to fast access to memory, less time consumed for context switching and hence overall effective memory management is done.

Multiplexing (sharing) of resources in the operating system is done in two different ways, these are; time multiplexing, and space multiplexing. When time multiplexing a resource, it involves the resources have different programs take turns in using them. So instead of one resource being dedicated

In a production MapR cluster, some nodes are typically dedicated to cluster coordination and management, and other nodes are tasked with data storage and processing duties. An edge node provides user access to the cluster, concentrating open user privileges on a single host. In smaller clusters, the work is not so specialized and a single node may perform data processing as well as cluster management. Cluster services often change over time, particularly as clusters scale up by adding nodes. Balancing resources to maximize cluster utilization is the goal, and it will require flexibility.

Scalable cache coherence protocols are essential for multiprocessor systems to satisfy the requirement for more dominant high-performance servers with shared memory. However, the small size of the directory cache of the increasingly bigger systems may result in recurrent directory entries evictions and, consequently, invalidations of cached blocks that will gravely corrupt system performance. According to prior studies, only a single core accesses a considerable fraction of data blocks, so it is needless to monitor these in the directory structure. Using the technique of uniprocessor systems and deactivating their consistency protocol is the best way to identify those private blocks actively. The directory caches will stop the tracking of a substantial amount of blocks after the deactivation of the protocol, which will minimize their load and enhance their adequate size. The proposal only needs minor changes because the operating system collaborates in finding the private blocks.

Abstract— There have been various cases where the processors sharing memory where one process reads and other writes when a processor is sharing is reading requires the memory to be used by various process but it does not create a problem when the process sharing memory are reading the memory the problem arises when the there is write operation is conducted. The write operation makes a change in memory which when utilized by another processor may requires use of previous value which may be not present now giving an error which has developed for the need of development of cache coherence which has it protocols implemented to prevent duplication, utilization, and updating of memory values used by various process in a control processing unit. Cache Coherence has various protocols that have been discussed are directory based, snooping, snarfing and distributed shared memory there have been various protocols that have been implanted in and new methods are being researched by various leading companies such as AMD, Nvidia, Intel and have been researched for better performance and solving issues. The paper discusses the various protocols used for implementation of cache coherence in processes.

2. Describe the role of the frame table and the disk map data structures in a demand paged memory manager.