Introduction to Parallel and Distributed Computing

<p>Network latency and bandwidth limitations (C)</p> Signup and view all the answers

<p>Enhance computational algorithms and system architectures (A)</p> Signup and view all the answers

<p>It enables efficient analysis of large datasets. (D)</p> Signup and view all the answers

<p>Apache Hadoop (B)</p> Signup and view all the answers

<p>Social media marketing (D)</p> Signup and view all the answers

<p>They define standards to ensure interoperability and security. (B)</p> Signup and view all the answers

<p>Managing synchronization and communication overhead. (C)</p> Signup and view all the answers

<p>Genetic data analysis across multiple machines. (C)</p> Signup and view all the answers

<p>Scalability and data availability (D)</p> Signup and view all the answers

<p>Google Cloud Platform (B)</p> Signup and view all the answers

<p>To distribute tasks evenly among processors or nodes. (B)</p> Signup and view all the answers

<p>The provision of distributed computing resources over the internet. (C)</p> Signup and view all the answers

<p>Fault tolerance and scalability (D)</p> Signup and view all the answers

<p>Graphical User Interface (GUI) (D)</p> Signup and view all the answers

<p>Netscape Navigator (A)</p> Signup and view all the answers

<p>Higher speed and efficiency (C)</p> Signup and view all the answers

<p>Network Era (B)</p> Signup and view all the answers

<p>It enabled scalable services over the internet. (C)</p> Signup and view all the answers

<p>Performance limited by a single processor's speed (A)</p> Signup and view all the answers

<p>Microprocessors (A)</p> Signup and view all the answers

<p>Clients interact with servers, enabling distributed computing. (B)</p> Signup and view all the answers

<p>To ensure messages are delivered correctly and in order (C)</p> Signup and view all the answers

<p>It ensures messages are delivered to multiple clients concurrently (C)</p> Signup and view all the answers

<p>To coordinate changes across multiple distributed components (C)</p> Signup and view all the answers

<p>They restore the system to a consistent state after failures (B)</p> Signup and view all the answers

<p>Increased Implementation Complexity (D)</p> Signup and view all the answers

<p>It aims to evenly distribute workloads (A)</p> Signup and view all the answers

<p>High resource utilization and reduced response times (D)</p> Signup and view all the answers

<p>Even distribution of computational tasks (B)</p> Signup and view all the answers

<p>It involves pre-determined assignment of tasks to resources. (C)</p> Signup and view all the answers

<p>Load-based (C)</p> Signup and view all the answers

<p>Dynamic mapping adapts to real-time changes in system conditions. (B)</p> Signup and view all the answers

<p>Optimistic concurrency control (B)</p> Signup and view all the answers

<p>Conflicts are resolved by comparing transaction timestamps. (C)</p> Signup and view all the answers

<p>It operates under the assumption that conflicts are rare. (C)</p> Signup and view all the answers

<p>To prevent other transactions from accessing data concurrently. (C)</p> Signup and view all the answers

<p>It continuously monitors system performance for task adjustments. (D)</p> Signup and view all the answers

<p>Threads share the same memory space but have their own execution context. (C)</p> Signup and view all the answers

<p>Programs tend to access a small subset of data frequently and nearby memory locations. (B)</p> Signup and view all the answers

<p>Memory latency and bandwidth. (B)</p> Signup and view all the answers

<p>Cache memory reduces the effective memory latency. (A)</p> Signup and view all the answers

<p>Data-intensive workloads such as scientific simulations. (B)</p> Signup and view all the answers

<p>It can further reduce effective memory latency. (C)</p> Signup and view all the answers

<p>Memory-bound applications. (D)</p> Signup and view all the answers

<p>Lower memory latency contributes to better system performance. (C)</p> Signup and view all the answers

Affordable and accessible computers for individual use.

Visual interfaces that make computers easier to use.

Revolutionized how we share information and communicate.

Distributed computing where clients interact with servers.

Tasks executed one after another, using a single processor.

Tasks executed simultaneously using multiple processors.

Set standards for PC hardware and software compatibility.

Computing services delivered over the internet, scalable resources.

Processing tasks across multiple computers (nodes) connected in a network.

Using internet-based services to store, process, and manage data.

Distributing content across multiple servers globally to improve website performance and reduce load times.

Distributing tasks evenly among processors or nodes to avoid congestion and ensure efficiency in parallel and distributed systems.

Time lost coordinating parallel tasks and communication between nodes.

Ensuring distributed systems can handle increasing workloads without performance loss.

Databases that store and process data across multiple computers.

The ability of a distributed system to continue operating correctly even if some nodes (computers) fail.

Ensuring that all copies of data in a distributed system are always synchronized and consistent, even when updates happen on different nodes.

Writing software for systems where multiple computers work together, making it more complex due to communication and coordination needs.

Ensuring that multiple computers working together update their data in a consistent and coordinated way.

Protecting distributed systems from attacks like unauthorized access, data breaches, or denial-of-service attempts.

The ability of a database spread across multiple computers to handle increasing amounts of data and users without significant performance degradation.

The time it takes for data to travel between computers in a distributed system, which can affect application responsiveness.

The ability of different computers and software in a distributed system to work together seamlessly, even if they are different.

Ensures messages between clients and servers are delivered correctly and in order, even with network failures or message loss.

Extends reliable communication to groups of processes in a distributed system, ensuring messages reach every member reliably, even with failures or network partitions.

Protocols that coordinate changes across multiple distributed components, ensuring consistency in distributed transactions. Like a global agreement.

Strategies to restore a system to a consistent and operational state after a fault or failure occurs. Like fixing a broken machine.

Improves performance, enables scalability, enhances fault tolerance, and ensures efficient resource utilization. A win-win for everyone.

To evenly distribute workloads across multiple resources, preventing bottlenecks and maximizing performance.

By distributing tasks, failures on one resource have less impact on the overall system.

Pre-determining task assignments to resources based on factors like capabilities, workload, and system layout. This mapping remains fixed unless manually changed.

A static mapping scheme that assigns tasks to resources in a sequential, circular order. Each resource gets a task in turn.

A static mapping scheme that assigns tasks to the resource with the fewest active connections, aiming to distribute workload evenly.

Adapting task assignments in real-time based on changing system conditions, like resource availability or network issues.

A dynamic mapping scheme that adjusts task assignments based on the current load on each resource. More loaded resources get fewer tasks.

Ensuring multiple transactions in a database system can execute concurrently without interfering with each other.

A concurrency control method where transactions acquire locks on data items, preventing other transactions from accessing them concurrently.

Assigning timestamps to transactions and determining their execution order based on the timestamps. Older transactions take precedence.

Different approaches to achieve concurrency, allowing multiple tasks to execute seemingly simultaneously.

Using multiple threads within a single process to achieve concurrency, sharing memory but with individual execution contexts.

Achieving concurrency through event-driven programming, where tasks are triggered by events or messages.

Different types of memory, organized hierarchically based on access speed and capacity, from fast registers to slow disk storage.

Programs tend to access a small subset of data frequently (temporal locality) or nearby data (spatial locality).

The time it takes to access data from memory, a potential bottleneck for performance, especially with large datasets.

The rate at which data can be transferred between memory and the processor, influencing system performance for memory-intensive tasks.

A small, fast memory between the processor and main memory, storing frequently accessed data and instructions to speed up access.