Programming Models – Sequential, Parallel, Concurrent, Distributed, Dataflow

Programming Models

Programming Models are basically frameworks or styles that help us decide how our program will run and how resources (like CPU, memory) will be managed.

1. Sequential Programming Model

What It Means:

Also called the Linear model. Here, program instructions run one after another in the exact order they are written.
Task B cannot start until Task A is finished.

Example:

Imagine you are cooking. First you cut vegetables (Task A), then fry them (Task B), and then serve (Task C). You cannot fry before cutting.

Key Point: It is single-threaded and the easiest to understand.

2. Parallel Programming Model

What It Means:

Multiple parts of the program run at the same time on different processors or cores.
Main goal is to increase speed.

Example:

On a construction site, many workers (processors/cores) are building walls, mixing cement, and painting at the same time.

Key Point: Good for tasks with lots of data where work can be divided.

3. Concurrent Programming Model

What It Means:

It looks like multiple tasks are running at the same time, even if only one processor is switching between tasks.
Processor quickly switches from Task A to B to C (context switching) creating an illusion of simultaneous execution.

Example:

On your phone, you can listen to music, browse, and download files at the same time. The processor switches fast between tasks.

Key Point: Focus is on managing tasks and reducing waiting time to keep the system responsive. Unlike parallel, it may use only one processor.

4. Distributed Programming Model

What It Means:

Program parts run on different machines connected via a network.
Like parallel programming, but processors are spread across multiple computers.

Example:

Think of Google Search. When you search, thousands of servers worldwide process your request simultaneously.

Key Point: Great for fault-tolerance (if one machine fails, others work) and scalability (handle many users).

5. Dataflow Programming Model

What It Means:

Execution does not follow instruction order but depends on data availability.
An operation runs only when its input data is ready. This is called "firing".

Example:

In Excel, if cell C has formula A+B, C updates only when A or B changes. Work happens only when data is available.

Key Point: Used in reactive systems and signal processing where data streams continuously arrive.

Model Focus / Execution Style Simple Definition
Sequential Order-dependent, one after another Finish one task, then start next
Parallel Speed / Multiple jobs at the same time on multiple cores Many tasks run together on different CPUs
Concurrent Responsiveness / Multiple tasks overlapping in time on one core Processor switches quickly between tasks
Distributed Fault-tolerance / Multiple tasks on networked machines Work is shared across the network
Dataflow Data-driven / Execution depends on data availability Tasks start only when data is ready

Comments

Post a Comment

Popular posts from this blog

Data Abstraction

Image
What is Data Abstraction? Data Abstraction ka matlab hota hai: “Sirf zaruri cheez dikhana, aur jo andar ki complex working hai usse chhupa dena.” Programming me hum user ko sirf “What to do” dikhate hain aur “How to do it” chhupa lete hain. Isse system simple, secure aur easy-to-use ban jaata hai.     Real-Life Example: TV Remote TV Remote abstraction ka perfect example hai. Aap remote me bas Volume Up , Channel Change , Power jaisa button dabate ho. Aapko nahi pata hota ki andar circuit kaise signal create karta hai, TV tak kaise pahuchta hai, software usse kaise process karta hai. Aapko sirf zaruri functionality dikh rahi hai → This is Abstraction! Agar company remote ki chip badal bhi de, aapka use karna same hi rahta hai. Programming Me Data Abstraction Coding me Data Abstraction ka matlab hota hai ki hum classes aur functions ko aise design karein ki: User ko sirf use karne layak functions dikhaye dein. Un functions ke andar kya logic chal raha hai, woh poora hid...
Read more

Data Structure Ka Parichay Aur Prakar (Introduction and Types of Data Structure)

Image
  1. Data Structure Ki Definition Data Structure ek logical aur systematic tareeka hai jisme data elements ko organize kiya jata hai taki essential operations jaise search, add aur delete efficiently kiye ja sake kam time aur memory mein. Simple Example: Ek library ko consider karo. Books (data) ko shelves (data structures) mein unke subjects ke hisaab se arrange kiya jata hai, taki jab aap koi book dhundho to turant mil jaye. 2. Data Structures Ke Prakar Data Structures mainly do categories mein divide hote hain: Primitive aur Non-Primitive . A. Primitive Data Structures Ye basic data types hote hain jo directly machine level par kaam karte hain. Programming languages inhe pre-defined provide karti hain. Integer (int): Poorn sankhyaon ko store karta hai. Example: 10, -5, 1000 Float/Double: Dashmlav sankhyaon ko store karta hai. Example: 3.14, 0.005 Character (char): Single akshar ya symbol store karta hai. Example: 'A', 'z', '9' Boolean (bo...
Read more

Data Abstraction

Image
  What is Data Abstraction? Data Abstraction means showing only the important information to the user and hiding all the internal working details. In simple words: Show what to do . Hide how it works . This makes a system easy to use, clean, and less confusing.   Real-Life Example: TV Remote When you use a TV remote: You only press buttons like Volume Up, Volume Down, or Channel Change. You do not see how the signal travels inside the remote, how the chip works, or how the TV processes the signal. You only see the basic functions. The internal working is hidden. This is called Abstraction . Data Abstraction in Programming In programming, abstraction means that: The user only sees the required functions or methods. The logic inside those functions remains hidden. Example: When you call saveData(data) in a program: You only know that the data will be saved. You do not know whether it is saved using SQL, NoSQL, a file system, or something else. The internal process is hidden fro...
Read more