(SEM VII) THEORY EXAMINATION 2024-25 HIGH PERFORMANCE COMPUTING

HIGH PERFORMANCE COMPUTING (KCS073)

B.Tech – Semester VII
 

Time: 3 Hours | Maximum Marks: 100

SECTION A (10 × 2 = 20 Marks)

(Attempt all questions in brief)

(a) Define Peer-to-Peer Computing with example.

Peer-to-Peer (P2P) computing is a distributed computing model in which all nodes have equal responsibility and can act as both client and server.
Example: File sharing applications like BitTorrent.

(b) Write about protocol and its importance.

A protocol is a set of rules that governs data communication between devices.
Protocols are important because they ensure correct data transfer, reliability, security, and interoperability between systems.

(c) Explain the term Open Grid in computing.

Open Grid refers to a grid computing environment that supports open standards and protocols, allowing resource sharing across different organizations and platforms.

(d) Why is security an important concern in computing?

Security is important to protect data confidentiality, integrity, and availability from unauthorized access, cyber-attacks, data loss, and misuse.

(e) How is a cluster built with network nodes?

A cluster is built by connecting multiple independent computers (nodes) using a high-speed network and configuring them to work as a single system.

(f) Write applications of clusters.

Clusters are used in scientific simulations, weather forecasting, data mining, financial modeling, and high-performance web servers.

(g) Explain the term Virtual Machine with example.

A Virtual Machine (VM) is a software-based computer that runs an operating system and applications like a physical machine.
Example: Running Linux on a Windows system using VirtualBox.

(h) State the use of software in clustering.

Clustering software manages job scheduling, resource allocation, communication, and fault tolerance among cluster nodes.

(i) Write the use of cloud in computing.

Cloud computing provides on-demand access to computing resources such as servers, storage, and applications over the internet.

(j) Explain the term storage with respect to cloud.

Cloud storage allows data to be stored, managed, and accessed remotely using cloud service providers like AWS, Azure, and Google Cloud.

SECTION B (Attempt any THREE) (3 × 10 = 30 Marks)

2(a) Describe the Grid Computing model and its protocols with diagram.

Grid computing is a distributed computing model that enables sharing of heterogeneous resources across multiple administrative domains.

Protocols used:

GridFTP

GRAM

MDS

These protocols handle resource discovery, job management, and data transfer.

2(b) Explain Open Grid Service Architecture (OGSA).

OGSA defines a service-oriented architecture for grid computing.
It integrates web services and grid technologies to provide interoperability, scalability, and resource sharing.

2(c) Components and classification of clusters.

Components:                                                        Compute nodes

Network                                                                  Storage

Cluster middleware

Classification:                                                        High Availability Clusters

Load Balancing Clusters                                          High Performance Computing Clusters

2(d) Parallel Virtual Machine (PVM) and its working.

PVM allows a collection of heterogeneous computers to function as a single parallel computer.
It uses message passing for communication.

Example: Scientific simulations running across multiple machines.

2(e) Types of clouds with examples.

Public Cloud: AWS, Azure                                       Private Cloud: Company-owned cloud

Hybrid Cloud: Combination of public and private

Community Cloud: Shared by organizations

SECTION C (Attempt any ONE) (1 × 10 = 10 Marks)

3(a) Architecture of High-Performance Grid with applications.

High-performance grid architecture includes:

Resource layer

Middleware

Application layer

Applications: Weather modeling, bioinformatics, and scientific research.

3(b) High-Performance Application Development Environment.

It includes tools for parallel programming, debugging, performance analysis, and libraries such as MPI and OpenMP.