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.
How Demand Paging manages physical memory limits and Page Faults.
What you just saw is called Paging.
Paging divides a process's Virtual Address Space into equal-sized blocks called Pages, and physical memory into identically sized slots called Frames. The Page Table sits between them, serving as a translation gateway that maps virtual coordinates to physical RAM.
But paging only tells us how memory is divided and mapped. The physical reality of computer hardware introduces a critical constraint: physical RAM is limited.
A process might have a vast Virtual Address Space (e.g., 4 GB on a 32-bit CPU), but the system may only possess a fraction of that in actual physical RAM. If multiple processes run concurrently, physical memory becomes even more scarce.
This discrepancy raises a fundamental question:
To resolve the physical limits of RAM, operating systems leverage Secondary Memory.
Secondary Memory refers to persistent storage devices, such as Solid-State Drives (SSDs) or traditional hard disks.
The differences between these two storage tiers shape how operating systems manage memory:
* Physical RAM: * Speed: Extremely fast (accessible in nanoseconds). * Direct Access: Connected directly to the CPU memory bus. * Capacity: Highly limited and expensive. * Volatility: Volatile (loses all data when power is removed). * Secondary Storage: * Speed: Much slower than RAM (accessible in microseconds or milliseconds). * Direct Access: Cannot be accessed directly by the CPU instructions. * Capacity: Much larger and significantly cheaper. * Volatility: Persistent (retains data when powered off).
The key insight is that a Page does not have to reside in physical RAM at every moment. Some Pages can be kept in Secondary Storage until they are explicitly needed by the CPU.
Instead of loading all Pages of a process into physical RAM immediately when the program starts, modern operating systems employ Demand Paging.
Consider a process with four Pages. Under Demand Paging, the memory state might look like this:
* Page 0 → Loaded in Physical RAM * Page 1 → Loaded in Physical RAM * Page 2 → Stored in Secondary Storage * Page 3 → Loaded in Physical RAM
Even though Page 2 is not currently resident in physical RAM, it remains a valid part of the process's Virtual Address Space. The Page Table keeps track of this status using a special flag called the Present (or Valid) Bit.
What happens if the CPU attempts to read an instruction or data located inside Page 2?
When the MMU queries the Page Table for Page 2, it detects that the Present Bit is set to 0 (Invalid/Not Present). The MMU cannot complete the translation. It halts the instruction and signals the processor:
This event is called a Page Fault.
A Page Fault is not a software crash or a programming error. It is a normal, expected control event that handoffs execution to the operating system to load the required page from disk.
Walk through the step-by-step sequence of a Page Fault.
In this scenario, the Virtual Address Space contains Pages 0 to 3. Frames 0 to 2 are occupied, while Frame 3 is free. Page 2 is currently stored in Secondary Storage. Watch what happens when the CPU requests Page 2:
Demand Paging allows the operating system to execute programs that are much larger than the physical RAM by loading pages dynamically as they are referenced.
But this strategy works smoothly only as long as there is an empty Frame available in RAM (like Frame 3 in our simulation) to receive the page.
What happens if the physical RAM is completely full?
Imagine this physical memory state: * Frame 0 rightarrow Occupied by Page A * Frame 1 rightarrow Occupied by Page B * Frame 2 rightarrow Occupied by Page C
Now, the CPU requests Page D, which is in Secondary Storage. There are no free frames left.
To bring Page D in, the operating system must first select one of the active pages (A, B, or C) to evict back to secondary storage to make room.
But how does it choose?
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."
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