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.
Experiment with intelligence beyond the cloud.
Can this image classifier maintain its intelligence while becoming small enough for the edge?
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.
Can this image classifier maintain its intelligence while becoming small enough for the edge?
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.
Explore the ideas, systems and connections that shape technology — choose any node to begin your journey.
Deploying neural networks and intelligent decision loops on raw silicon targets.
Understanding the system-call boundary and file descriptors.
When writing code to interact with persistent storage, we often start with a simple command:
To a programmer starting out, it is easy to assume a direct, unmediated relationship: the application requests a file, grabs it, and reads or writes its bytes directly from the disk.
But this mental model is an illusion.
An application cannot directly access physical storage devices. The CPU runs program code in a restricted, unprivileged mode (User Mode). In this execution space, program instructions cannot issue raw commands to storage interfaces. If an application could touch storage sectors directly, a single bug or malicious loop in one program could overwrite the partition table, corrupting the entire system.
To interact with a file, the application must cross a strict architectural boundary.
To access a file, the program must request the operating system kernel to perform the operation on its behalf. It does this by using a set of dedicated functions called System Calls.
These calls represent the secure interface through which applications query the kernel:
* open(): Requests access to a file by name.
* read(): Requests bytes from a previously opened file resource.
* write(): Requests bytes into a previously opened file resource.
* close(): Releases the resource.
It is important to make a conceptual distinction: these system calls are not File Management itself. They are simply the API—the doors in the wall. File Management is the massive, complex infrastructure running inside the kernel that handles access verification, data buffering, filesystem block mapping, and storage scheduling behind those doors.
When an application invokes open("notes.txt"), the kernel does not send the physical file data to the application. Instead, if the request is valid, the kernel returns a simple integer:
This integer is a File Descriptor (often abbreviated as fd).
The application does not receive a pointer to raw storage or the filesystem structures. It receives a reference index. When the application needs to read data, it passes this index back to the kernel:
Conceptually, we must separate three distinct ideas:
* The File: The persistent resource resting on storage (defined by its metadata/inode and data blocks). * The Open File (Description): The temporary tracking state allocated by the kernel when a file is opened (storing the current read/write cursor offset, access flags, and links to the file metadata). * The File Descriptor: The process-specific integer index that references the kernel's open-file table.
The application holds only the descriptor index. The operating system retains complete control over the file state.
Watch the interactive sequence below to see how execution transitions across the system-call boundary, how descriptors are mapped in the process table, and how the kernel tracks file offsets:
Because descriptors are private indexes mapped inside a process's file descriptor table, different processes have separate descriptor namespaces.
If Process A and Process B both open "notes.txt" independently, they do not automatically share the same open file state:
Each process receives its own descriptor (which might happen to be the same integer, e.g. 3) mapping to a separate Open File entry in the kernel's global table. Each entry maintains its own read/write cursor offset. If Process A reads 10 bytes, its offset advances to 10, while Process B's offset remains at 0.
However, in certain scenarios (such as when a process forks or passes descriptor references through IPC), different processes can share the exact same kernel-managed open file state. In that case, an offset advance by one process directly affects where the other process will read or write next.
File descriptors belong to individual processes, but open-file states and files are distinct kernel-wide resources.
The exact names and mechanisms for this reference system differ across operating systems, but the underlying architectural pattern is identical:
* Unix / Linux / POSIX: Relies on integer-based File Descriptors. Standard streams are pre-allocated: 0 (stdin), 1 (stdout), and 2 (stderr).
* Windows: Applications invoke APIs like CreateFile() and receive a HANDLE (a pointer-sized opaque reference) rather than a small integer.
In both paradigms, the application receives a reference token. The process never interacts with the storage driver directly; it requests operations using the token, and the operating system handles the translation.
We now understand that an application does not directly hold the physical file. It uses a file descriptor or reference index to ask the operating system to perform operations on the file. The kernel maintains the open file state and delegates block lookup to the filesystem.
But this relies on the file already being identified by name.
When the application requests:
/usr/local/bin/prog
How does the filesystem find the file that this name refers to?
PrajnaEdge is a technology company exploring the space between understanding technology, experimenting with ideas, and turning them into things that can be experienced.
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.
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.
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 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.
Software that runs directly on hardware without an operating system.
"Every embedded application begins long before main()."
An Operating System manages hardware and software resources so complex applications can work efficiently.
"When one loop is no longer enough to carry the burden."
PrajnaEdge is an independent education platform built to make knowledge freely accessible.
If you find PrajnaEdge useful, you can support its continued development.
Your support helps fund the time, tools, infrastructure, and experimentation that go into building and maintaining PrajnaEdge.
Welcome to PrajnaEdge (prajnaedge.dev), an independent engineering and technology platform created and maintained by Devaharsha Meesarapu. By using this website, you agree to these terms.
Educational & Research Focus: PrajnaEdge publishes interactive technical explorations, architectural models, and simulation walk-throughs covering embedded systems, computer architecture, operating systems, and edge artificial intelligence. All materials, interactive tools, and code demonstrations are provided solely for educational and conceptual understanding.
Hardware & Firmware Disclaimer: Embedded programming interacts directly with hardware registers, physical voltages, and precise timing. While all writeups and code demonstrations are prepared with care, they are provided "as is" without warranty of any kind. You are responsible for reviewing component datasheets, circuit schematics, and electrical ratings before deploying code to physical microcontrollers or custom hardware.
Intellectual Property: All original articles, custom SVG architectures, interactive simulators, curriculum sequences, and source code are the intellectual property of Devaharsha Meesarapu (© 2026 PrajnaEdge. All rights reserved). Non-commercial educational study and citation are welcome with proper attribution. Direct republication, unauthorized mirroring, or mass scraping of content is not permitted.
PrajnaEdge is committed to user privacy and minimal data collection. We do not sell, rent, or monetize your personal information.
localStorage purely to remember your interface preferences on your device (such as sound preferences for animations and tutorial display states). No personal identity data is stored in localStorage.
To help support platform operation and hosting, PrajnaEdge displays advertisements served by third-party advertising partners, including Google AdSense.
We use Google Analytics (measurement tag: G-6Y8ZVQB1V0) to evaluate anonymous, aggregate usage trends across our technical writeups.
Depending on your jurisdiction (including rights under GDPR, CCPA/CPRA, and applicable privacy laws), you have the right to request access to, correction of, or deletion of any personal communications you have submitted. We do not sell personal data.
For any questions regarding these terms, privacy practices, or data inquiries, contact the creator directly: