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For the last few weeks, I've been writing a multi-CPU single-board computer like explorer. I'm calling it CROSSWOZ (Hat tip to Woz and the WOZMON). Seven vintage CPU cores (6502, 65C02, Z80, 8080, 8085, 6809, 1802) share a 64K memory bus and the same WOZMON-style monitor. I can swap...

14,998 просмотров • 2 месяцев назад •via X (Twitter)

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*** SEGA GENESIS/MEGADRIVE - SCALING PART 2 *** Whats better on a Friday than seeing some scaling effects on the Megadrive ? .. nothing, so read on ... In the previous part we were software scaling in either axis by a given factor, but I couldn't change the scale factor per scanline on the same frame, so I couldn't skew the base image for tilting into screen eg Mode 7 type effects. - One issue was it was scaling column by column which got wrecked for performance trying per scanline adjustments. So I converted to a row scaler rather than column, this allowed expansions and contractions on a per scanline basis. - Speed up the code significantly , now running a sprite load + music + scaling on cpu with ~50% cpu free. Relied heavily on Python scripts I wrote to generate the 68k assembly for this as it was mind numbing labourious. In doing so I got the scripts competing with each other to come up with the fastest method for each scale , I'm starting to like python ;-) - Tried all sorts to speed up the horizontal interupt - handles vertical scaling, exotic methods eg unsafe interupts / racing the beam & updating the vertical scroll every X cpu cycles, in the end the Z80 cpu (audio) stealing the 68k cpu bus intermittendly just killed these ideas as it would only be 95% stable, ended up just doing smarter interupts that saved a lot of cpu instead. - The good and the bad, spent too long on this is the bad, the good is we will need it in Lufthoheit in a few places to make up for that !! Carsten666 CYBERDEOUS - Crouzet Laurent #SGDK #SegaMegadrive #SegaGenesis

Shannon Birt

11,070 просмотров • 1 год назад

Jensen Huang just identified the next $200 billion market (Save this). The shift starts with a observation about agentic AI that changes everything about infrastructure. In the era of training and inference, the GPU was everything while CPU was a traffic cop, scheduling work, managing memory, dispatching tasks while the GPU did the heavy lifting. Agentic AI breaks that model entirely. An AI agent does not just run a single inference pass but rather it plans, calls tools, executes code in sandboxes, retrieves data from multiple sources and loops through complex multi-step reasoning sequences often thousands of times per second at scale. Every one of those operations runs through the CPU and the GPU sits idle waiting for the CPU to prepare the next task, supply the right context and execute the retrieval and tool calling logic fast enough to keep the accelerators fed. The CPU is now the conductor and the GPU is the orchestra and the bottleneck is the conductor falling behind. This is showing up in production AI factory utilization right now, which is exactly why Jensen built Vera from scratch rather than licensing x86. Vera achieves 40% lower peak memory latency than x86, 50% faster core to core communication, and 1.8 times the agentic sandbox performance of current x86 processors on a purpose-built architecture designed around the agentic loop. Now here is where the investment thesis gets interesting. The obvious beneficiary is Nvidia itself, and that thesis is real. Nvidia's CFO has guided for nearly $20 billion in Vera CPU revenue this fiscal year alone, a market Nvidia had zero presence in just three years ago. Intel held 60% of server CPU market share as recently as Q4 2025 and that transition is now happening at a pace Intel structurally cannot respond to. But the deeper question is, what architecture is Vera actually built on? Vera's Olympus cores are ARM compatible and every single Vera CPU deployed in every Vera Rubin rack in every data center in the world runs on ARM architecture. And ARM Holdings collects a royalty on every one of them. ARM does not make chips but rather licenses the instruction set architecture and CPU core designs that others build on top of. Every time Nvidia ships a Vera CPU, every time a hyperscaler deploys a Vera Rubin rack, every time an enterprise qualifies Vera for their AI factory, ARM earns a royalty. The secular tailwind here is almost perfectly constructed for ARM's business model. Amazon's Graviton, Microsoft's Cobalt, Google's Axion, Apple's silicon stack, and Qualcomm's data center push all run on ARM. And now Nvidia's Vera, which is projected to displace Intel as the largest server CPU supplier by revenue in a single fiscal year, is ARM. ARM's royalty rate on high end server chips is estimated at roughly 1 to 2% of chip selling price. At $5,000 per Vera CPU and 4 million units projected for FY2027, that is a royalty line growing from near zero to potentially $400 million to $800 million annually from Nvidia's data center CPU business alone before counting Amazon, Microsoft, Google, Apple, and Qualcomm. The total ARM addressable royalty base across all the silicon it already licenses is compounding at a rate that the current $130 billion market cap does not fully reflect. Jensen's CPU thesis is the most underappreciated catalyst in ARM's fundamental story, and the royalty compounding has barely started. Come join Milk Road Pro and get our full ARM royalty model and our entire AI trade thesis. Link below!

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11,819 просмотров • 1 месяц назад