PrajnaEdge
A curiosphere for curious minds who want to understand, experiment with, and experience technology.

Technology is a system of connections.

Modern technology is built from layers that continuously interact with one another. At the physical level, electronic devices transform electrical signals into digital information. Digital logic turns that information into computation, while processors, memory and communication interfaces provide the machinery needed to execute instructions and move data. As these components become part of embedded systems, they begin to interact with the physical world through sensors, controllers, actuators and real-time software.

But computation does not exist in isolation. Operating systems coordinate hardware and software, firmware gives specialized machines their behaviour, and communication protocols allow independent systems to exchange information. At the same time, machine learning is moving beyond the cloud into edge and on-device systems, where models must operate within real constraints such as memory, processing power, latency and energy consumption.

PrajnaEdge explores these connections as one continuous technology landscape — and takes them beyond explanation. From computing foundations and embedded systems to intelligent machines and edge AI, ideas can be understood, experimented with, and eventually turned into technology that can be experienced in the real world.

To continue exploring
Products

Technology, made tangible.

PrajnaEdge products and technology experiences are currently in development.
In Development

Playground

Experiment with intelligence beyond the cloud.

AI runs closer to where data is generated — reducing dependence on distant cloud infrastructure and enabling faster, more responsive systems.
Edge AI Computer Vision

Image Classification

Can this image classifier maintain its intelligence while becoming small enough for the edge?

On-Device AI Coming later

On-Device Intelligence

AI runs directly on the device where data is generated, bringing intelligence into the device itself while operating within its compute, memory, power and latency constraints.

Edge AI Playground

Image Classification

Can this image classifier maintain its intelligence while becoming small enough for the edge?

Choose an image

Upload an image
Supports JPG, JPEG, PNG
This classifier recognizes only Apple, Banana, and Orange. Other objects may be incorrectly classified as one of these classes.

Choose the model

Model size
4.91 MiB
Largest activation
~625 KiB
Test accuracy
99.11%
Measured model accuracy
Your image is processed locally in your browser.
Playground · Future Area

On-Device AI

AI runs directly on the device where data is generated, bringing intelligence into the device itself while operating within its compute, memory, power and latency constraints.

Coming later

Explore the ideas, systems and connections that shape technology — choose any node to begin your journey.

PrajnaEdge Navigation Tree
Embedded Systems Tree

Edge AI Demonstrations

Deploying neural networks and intelligent decision loops on raw silicon targets.

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Operating Systems

Choosing What to Forget

When physical memory is full, which page must be evicted?

Operating SystemsMemory ManagementPage ReplacementFIFOLRUOptimal

1. The Saturation Point

Imagine a system running under constraint. Its physical RAM is small, containing only 3 physical frames. Right now, physical memory is completely saturated, filled with three active pages:

RAM Frames: [ Page 2 | Page 5 | Page 7 ]

A thread executes an instruction requesting virtual address space residing in Page 3.

The MMU looks up the translation in the Page Table, finds it invalid, and raises a Page Fault. The Operating System traps the fault and prepares to copy Page 3 from disk into RAM. But there is a bottleneck: all physical frames are occupied.

To resolve the fault and bring Page 3 into memory, the operating system must choose one page currently in RAM and evict it back to disk.

This decision is known as Page Replacement.

2. Three Answers to the Same Question

How do we decide which page should leave? The policy we choose determines our system's memory efficiency. Three core algorithms answer this question:

First-In, First-Out (FIFO) "Which Page arrived first?" Evict the oldest page loaded into RAM, regardless of how frequently it is being used.

Least Recently Used (LRU) "Which Page has been unused the longest?" Evict the page that has not been accessed for the longest duration, relying on the principle of temporal locality.

Optimal (OPT) "Which Page will be needed farthest in the future?" Evict the page that will go the longest before being requested again.

3. Interactive Page Replacement Simulator

See how these three different strategies handle the exact same reference sequence under the same constraint:

Reference Sequence: 1 → 2 → 3 → 1 → 4

Observe how the exact same access trace produces completely different eviction choices and page fault rates depending on the active policy.

The Mathematical Ideal vs. Hardware Reality

The Optimal policy represents the absolute ceiling of performance, guaranteeing the minimum possible Page Faults for any known reference sequence. However, in practice, a real-world operating system cannot implement the Optimal policy because it cannot know future memory references in advance. Real-world systems must approximate this behavior using historical data, making LRU the standard benchmark for practical implementation.

4. Manthana: The Paging Boundary

We have learned how Paging places fixed-size pages into physical frames. We have also learned how Page Replacement decides which page should leave when all frames are occupied.

But notice something important: all of this assumes that memory is being managed as fixed-size pages.

What happens when a program needs memory as a meaningful, variable-sized unit rather than as a collection of equal-sized pages?

What if memory management followed the logical structure of the program itself?

System Tree Node Operating Systems

PrajnaEdge

Engineering concepts you don't just read — you experience.
Founded in 2026.

PrajnaEdge is a technology company exploring the space between understanding technology, experimenting with ideas, and turning them into things that can be experienced.

Our Mission

To make technology easier to explore, deeper to understand, and more exciting to experience.

Our Vision

To build a technology ecosystem where curiosity, experimentation and creation continuously lead to one another.

Where it began

Embedded Systems

PrajnaEdge began with Embedded Systems — exploring the foundations that connect hardware, software and intelligent computation.

The first technology universe is built around that foundation. The journey will expand as new ideas, experiments and products emerge.

PrajnaEdge is a technology company created by Devaharsha Meesarapu.

CREATOR PROFILE

Devaharsha Meesarapu

Embedded Systems • Firmware • Edge AI

I am the engineer behind the design, development, and content of PrajnaEdge. I build low-level systems where code directly controls hardware, bridging the gap between register-level silicon behavior and intelligent edge decision loops.

View Resume →

ABOUT ME

I am an Embedded Firmware Engineer focused on developing software for resource-constrained systems. My experience spans bare-metal firmware, device drivers, microcontroller peripherals, and communication protocols, working across the boundary between hardware and software.

My work has involved microcontroller-based systems, real-time behaviour, hardware interfaces, and communication technologies such as CAN, CAN FD, UART, SPI, and I²C. I am particularly interested in understanding systems from the lowest level upward—from registers and peripherals to intelligent edge systems.

ENGINEERING PHILOSOPHY

Engineering is not just about writing code; it is about managing constraints, timings, and physical hardware characteristics. True mastery of complex systems comes from understanding the interactions across different layers of the stack.

This conviction is why I built PrajnaEdge—to bridge the gap between conceptual theory and direct, register-level physical reality.

CONNECT

LinkedIn → GitHub →

Interactive Career Journey

BTech · ECE

Foundations

Where it all began — understanding the physical layer of computation. Circuits, signals, and systems gave me a mental model of how information moves through hardware.

⬡
Connects to Systems
Understanding circuits directly enables writing firmware that talks to peripherals at the register level.
What it is
BTech in Electronics and Communication
Undergraduate foundation covering analog & digital circuits, signal processing, microprocessors, and communication systems.
CircuitsSignal ProcessingMicroprocessorsVLSI
What I did
Core Engineering Fundamentals
Studied semiconductor physics, digital logic design, and embedded microcontrollers. Built prototypes using 8-bit MCUs.
8051Logic DesignPCB Basics
What I learned
The Hardware Mental Model
Every software abstraction sits on physical reality. Understanding silicon teaches you why timing, power, and noise are first-class engineering problems.
Let's Connect
Interested in embedded systems, AI, or building something meaningful? I'd love to hear from you.
Open to collaborations, research, and interesting engineering conversations.
Help Improve PrajnaEdge
Found something to improve? I'd love to hear your thoughts.

Bare Metal

Software that runs directly on hardware without an operating system.

Applications
↑
Operating Systems
YOU ARE HERE
Bare Metal
Processor
↑
Hardware

"Every embedded application begins long before main()."

Operating Systems

An Operating System manages hardware and software resources so complex applications can work efficiently.

Applications
↑
YOU ARE HERE
Operating Systems
Bare Metal
↑
Processor
↑
Hardware

"When one loop is no longer enough to carry the burden."

← Return to Systems Tree
Select Domain
Explore application domains branching from the Systems Tree
Automotive
Aerospace & Defence
Consumer
Embedded AI
Industrial
Medical
Multimedia
Network & Connectivity
Robotics
Explore Active Systems Tree →
← Return to Systems Tree
Select Depth
Examine computation through architectural depth layers
Architecture
Controller
Digital
Programming
Processor
Explore Processors → Explore Controllers →

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