Tyler took his time, using nearly the entire day to outline his plans for the fabrication plant. Each detail had to be precise. There was no room for sloppiness or oversight.
What he was attempting—creating a GPU ten times more powerful than the Blackwell chip from his previous life—was, by all standards, a technological leap that shouldn't be possible for another 30 to 50 years.
The sheer audacity of it would have earned him ridicule in any academic circle, if he were foolish enough to tell anyone.
Creating a GPU, even the current generation in 2010 that used 40nm chips, was already an incredibly complex and delicate undertaking.
Fabrication required multi-billion-dollar cleanroom facilities, photolithography equipment, deposition chambers, and atomic precision. The margin for error was measured in atoms.
And yet, Blackwell, the most advanced GPU of his previous timeline, had gone far beyond that. Its architecture was based on a 3nm process node, containing over 100 billion transistors.
It ran on an advanced multi-layer parallel structure capable of exceeding 1,000 teraflops in peak performance. The cost of production alone was astronomical.
Each Blackwell chip required an entire ecosystem of bleeding-edge machines—extreme ultraviolet (EUV) lithography tools priced at over $150 million apiece, deposition systems that relied on atomic layer precision, and custom-built etching chambers capable of dealing with ultra-thin gate oxide materials.
The advancements that made Blackwell possible weren't singular—they were layered:
Transistor Design Evolution: The introduction of gate-all-around FETs to replace traditional FinFETs, improving leakage and scalability.
Photolithography Advancements: EUV allowed for etching patterns at sub-10nm resolution without relying on complex multi-patterning techniques.
Material Innovations: The use of new semiconductors such as molybdenum disulfide, silicon-germanium channels, and graphene-based interconnects.
Etching and Deposition Precision: Atomically-accurate plasma etching and deposition allowed engineers to build intricate 3D structures without defects.
Multi-Patterning and Mask Engineering: Improved techniques for mask alignment, phase-shift masking, and source-mask optimization became standard.
Quantum Tunneling Mitigation: The management of electron leakage due to quantum tunneling was achieved through ultra-thin insulators and material engineering.
The total cost to produce the Blackwell chip? Upwards of $700 million in R&D, $400 million in fabrication infrastructure, and over $10,000 per chip in raw production.
But Tyler didn't have that.
He didn't have time to build quantum dot transistors from scratch. He didn't have access to EUV machines or billion-dollar facilities—at least not yet.
So instead of trying to mimic what had already been done, he set out to achieve the same outcome through a different path. One rooted in the deep, abstract understanding unlocked by [Computational Mathematics].
With the Specialised Knowledges now flowing through his mind like a living organism, Tyler began constructing an alternative method.
He would use optimization algorithms and graph theory to completely redesign the way 40nm transistors were laid out.
Instead of increasing transistor density through smaller nodes, he would maximize the utility of every existing transistor.
Through a technique he coined temporal multiplexing, each transistor would be configured to handle multiple data streams over time by dynamically shifting its role in the processing sequence.
In essence, each transistor would behave like many, drastically amplifying output.
The result? A theoretical throughput of 1,500 teraflops on a 40nm process.
Then came the question of quantum tunneling—the electron leakage that made high-density chips unstable at small sizes.
At 40nm, this shouldn't have been a major issue, but Tyler intended to push 40nm far past its theoretical performance limit.
His solution: the Quantum Compensation Algorithm.
Using specialized knowledge of electron wave functions, he built an adaptive model that predicted tunneling probabilities between closely packed transistors.
By mathematically aligning transistor gates in a specific geometric layout, the wave interference patterns would cancel out, reducing leakage and maintaining signal integrity.
This wasn't just theory. The algorithm modeled the energy barriers, adjusted gate widths, and tuned oxide thickness to precisely control electron flow.
It was like tuning a million microscopic floodgates with surgical precision—knowing exactly when electrons would slip through, and when they wouldn't.
With it, he could run his 40nm transistors at clock speeds of 50 GHz without catastrophic heat that could cause the chip to melt, or become unstable.
The next challenge was achieving 3nm-like precision using 40nm fabrication equipment. Tyler knew his future fab wouldn't have EUV machines, so he needed an alternative.
He developed a set of advanced patterning algorithms that exploited the physics of light diffraction.
By fine-tuning the exposure wavelengths and angles during photolithography, his software could guide even legacy DUV equipment to etch sub-20nm patterns reliably.
Each diffraction pattern was simulated in real-time, accounting for lens aberrations, resist behavior, and etch bias.
These were then used to adjust the exposure mask dynamically. In practice, it meant his 40nm fab would be capable of etching features nearly five times smaller than what the machine was designed for.
And he wasn't done.
His most radical move was to incorporate non-traditional computing paradigms into the design.
He was going to build neuromorphic circuits—a feat that most of the world's top researchers hadn't cracked.
Neuromorphic chips emulate the brain. Each transistor becomes a neuron, each circuit a neural path. They don't run on linear instructions; they fire signals in a web of weighted connections.
The problem? They're near impossible to simulate, let alone fabricate, using traditional chip design tools.
But Tyler had more than tools.
He had Autonomous Compiler Design, Deep-State Pipeline Coordination, and Fractal Compute Structures under his belt.
Using those, he wrote an entirely new compiler that translated would be a high-level AI functions into chip-level neuromorphic configurations.
He built a simulation framework capable of emulating billions of synaptic interactions in real time.
And to run all of this? He would need to address power and heat.
Enter: the Thermal Equilibrium Optimization Algorithm.
It modeled heat dissipation and power delivery down to the transistor level, predicting hotspots before they happened.
It allowed the chip to dynamically reroute current flows, prioritize low-power transistors during intensive loads, and scale clock speeds on a per-core basis.
Result: a minimum of 1,500 teraflops performance on ~200 watts of power, achieved without advanced cooling systems.
When Tyler finally closed his notebook filled with extremely and mind boggling algorithms, and his GPU's blueprint, the sun was already low on the horizon.
He exhaled slowly, shoulders relaxing as he reviewed the layers of his plan.
He had done it.
He had sketched out a viable blueprint to build a fabrication plant capable of producing GPUs that didn't just rival Blackwell, but would dwarf it.
If he hadn't done it like that—using algorithms created with [Computational Mathematics] specialised knowledges, then he would definitely need to unlock the [Physics] core knowledge branch, unlock related primary knowledge branches and purchase their specialised knowledges.
This helped him to reduce cost drastically—both for the knowledge needed but also the production cost for the GPU.
As for production cost and cost for setting up the fabrication plant, though he won't be spending tens of billions for it but he will still be spending billions. And his estimate was $4B.
Not only that, he'd need location—which he already solved with Gumua, radiation-free materials, a supply chain tighter than the NSA's vault system, and a workforce that wouldn't leak even under waterboarding.
Satisfied with what he had achieved, Tyler stood up and stretched, his joints cracking lightly from the long hours spent at the desk.
His body felt good. There was no lingering pain, as the side effects from the knowledge absorption had passed since early in the morning.
He glanced at the notes one last time before arranging them neatly beside his closed laptop.
The study was bathed in the warm gold of evening light, silent except for the hum of the AC.
With the hardest part of the day done, he left the study and headed downstairs. Now, it was time to test his new limits.
He made his way to the personal gym. After all, he hadn't checked what had changed with the stat upgrades. Intelligence had hit 20. Stamina, 15. And Strength and Agility had received boosts as well.
It was time to see how his body had evolved.