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.

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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.

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Embedded Systems Tree

Edge AI Demonstrations

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

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Operating Systems

The Disk Has No Files

Deconstructing storage stacks, partition tables, and directory tree attachments.

Operating SystemsStorage ManagementPartitionsMountingStorage Stack

1. Start with the Familiar Assumption

When you open your computer's file explorer, you see your documents organized neatly:

notes.txt photo.jpg resume.pdf

It is natural to assume that these files are written directly onto the storage disk in the same way they are represented on your screen.

But this mental model is incorrect.

Fundamentally, a physical storage device has no concept of a "file," a "directory," a "path," or "file permissions." If you inspect the copper lines of an NVMe drive or the magnetic platter of a hard disk, you will not find folders or names.

A raw storage device provides only a flat sequence of addressable sectors. Every structure—from files to directories—is a virtual arrangement created and maintained entirely by operating system software.

2. Reveal the Storage Stack

To bridge the gap between human concepts and physical hardware, operating systems organize storage into a layered hierarchy called the Storage Stack:

Application Layer Calls open(), read(), write() API commands Logical File Abstraction Treats data as a continuous byte stream Filesystem Driver Manages directories, indexes, and block mapping Partition / Volume Defines boundary limits on physical storage Block Device Interface Handles block read/write commands (LBA) Physical Storage Media HDD platters, SATA, NVMe flash cells

* Application: Requests file operations using path names (open("/home/user/notes.txt")). * Logical File: Exposes the file stream to applications, hiding block offsets. * Filesystem: Translates paths into internal IDs (inodes/MFT records) and maps logical offsets to LBA storage block sectors. * Partition / Volume: Defines the boundaries of a raw disk space allocated to a single logical driver. * Block Device Interface: The operating system subsystem that manages block-oriented command flows. * Physical Storage Media: The actual hardware sectors that store charge states or magnetic orientation.

3. Raw Storage

At the lowest level, a storage device is a flat array of addressable slots called Logical Block Addresses (LBAs):

RAW STORAGE LBA LIST [000][001][002][003][004][005][006][007][008]...

At this raw layer, files like notes.txt or photo.jpg do not exist. There are only index numbers. The OS reads or writes data by specifying the exact block index (e.g. "Read LBA block 120").

The filesystem is the organization layer that compiles these raw addresses into a structured digital workspace.

4. Formatting / Creating a Filesystem

Creating a filesystem—often referred to as formatting—is the step that establishes these directory and index tables on the raw storage media.

RAW DEVICE ↓ Filesystem Creation (Format) ↓ Bookkeeping Tables Initialized (Superblock, Bitmaps, Inodes) ↓ Files / Directories / Free Space Ready

Formatting does not necessarily mean overwriting every single sector of the physical disk with zeros (which is a "Full Format"). Instead, a standard format simply initializes the master filesystem index tables, rendering the rest of the block addresses as empty space ready for reuse.

5. Partitions and Volumes

Before writing a filesystem index, raw disks are usually divided into independent virtual zones called partitions:

Physical Drive Allocation Layout Partition 1 (LBA 00–47) Partition 2 (LBA 48–59) Unallocated Ext4 Filesystem (Linux /home) FAT32 Filesystem (EFI System)

A partition represents a designated range of consecutive physical sectors reserved on the disk (e.g. LBA 00 to 47). This boundary allows a single storage drive to host multiple operating systems, separate configurations, or isolate user data from system binaries.

6. EdgeCase: From Raw Device to Filesystem

Use the simulator below to track how raw blocks are virtualized step-by-step into partitions, initialized with metadata indexes, and layered with file abstractions:

7. Important Distinction: Partition vs Filesystem

Understanding the boundary between partitions and filesystems is essential:

* Partition: Answers: Which sectors of the physical media belong to this volume boundary? It is defined by partition tables (like GPT or MBR) written at the start of the drive. * Filesystem: Answers: How should the sectors within this partition be structured into directories, metadata tables, and files?

A partition sets the physical playground limits; a filesystem establishes the rules of the game played inside.

8. Mounting

To make a filesystem accessible to applications, the operating system must attach it to its logical namespace—a process called mounting:

Storage Volume ↓ Filesystem Structures ↓ Mount Point ↓ OS Directory Tree Namespace ↓ Application

* Unix / Linux: Attach filesystems into a unified directory tree. For example, Partition 1 (/dev/nvme0n1p1) might be mounted at /, while a USB drive is mounted at /media/usb. * Windows: Exposes mounted partitions using drive letters (C:, D:) or paths.

Mounting takes the self-contained block structures of a filesystem volume and plugs them into the active directory structure.

9. Real Operating-System Connection

Production kernels use abstraction layers to ensure applications can access different filesystems uniformly:

* Linux (Virtual File System - VFS): VFS acts as a common interface layer. When an application calls read(), VFS intercepts it and translates the request into the appropriate filesystem driver call (e.g. ext4, FAT, or NTFS), which in turn requests data blocks from the device driver. * Windows (I/O Manager & Filter Drivers): A similar stack manages I/O requests, sending them down through filesystem filter drivers to logical volume managers and port drivers.

The layered architecture ensures that application developers write programs targeting files, rather than hardcoding disk sector commands.

10. HDD vs SSD/NVMe

The physical media underneath the block interface dictates how fast blocks can be read and written:

Hard Disk Drives (HDDs) Store data magnetically on spinning platters. Because a mechanical read head must physically travel to specific sector tracks, HDDs suffer from high latency (seek time and rotational delay) and perform sequential accesses much faster than random ones.

Solid State Drives (SSDs) Store data in flash memory cells. Since there are no moving parts, random reads are extremely fast. However, writes require erasing blocks before they can be rewritten, which requires internal wear leveling and block relocations.

NVMe SSDs Use the high-speed PCI Express (PCIe) bus rather than old SATA controller pathways, allowing thousands of parallel command queues to reduce I/O bottlenecks.

Regardless of the underlying hardware technology, the filesystem presents the same unified file abstraction to the operating system.

11. The Next Question

We have now crossed the boundary from files and filesystems into the storage device itself.

But storage requests do not all arrive in the same order, and on some devices the physical cost of serving those requests can be enormous.

When many storage requests are waiting, how should the operating system decide which one to serve first?

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."

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