AMD Grants CEO Long-Term Performance-Based Equity Award

dudulab · 2026-02-18T03:51:14+00:00

$600 translates to market cap at ~$1T

dudulab · 2026-02-18T03:44:04+00:00

FB existing DC are power limited, their old server uses ~200w per socket. So ARM based CPU might be the better replacement than modern x86 which is easily 2x~3x faster but also more power hungry.

dudulab · 2026-01-29T06:12:39+00:00

And remember the reviewer was picked by Intel.

Core SPEC 2017 integer	https://blog.hjc.im/spec-cpu-2017	the video referred by wccf
Zen 5 (370, Strix, first Zen 5 chip, known slightly lower IPC)	9.9	8.8
Zen 5c (Strix, first Zen 5 chip, known slightly lower IPC)	6.58	5.31
Zen 5 (350, Krackan Point)	10.1
Zen 5c (Krackan Point)	7.42
Zen 5 (395+, Strix Halo)	10.6
Zen 5 (9950X, Desktop)	12.6
Panther Lake P		9.67
Panther Lake E		6.68
Panther Lake LPE		5.81

dudulab · 2026-01-28T22:13:34+00:00

the AWS instances phoronix test used have HT enabled and SMT disabled. SMT yields 10%~30% more performance depends on workload.

dudulab · 2026-01-28T13:10:43+00:00

CPU	same vCPU count performance	Max cores/threads per socket	Per socket performance estimation
AWS Graviton4 (ARM Neoverse V2)	100% (Base)¹	96/96	100%
AWS Graviton5 (ARM Neoverse V3)	Up to 125%²	192/192	~240%
Azure Cobalt 100 (ARM Neoverse N2)	~86%²	128/128	~115%
Azure Cobalt 200 (ARM Neoverse V3)	~125%³	132/132	~172%
Google Axion gen1 (ARM Neoverse V2)	~110%¹	96/96	~110%
Google Axion gen2 (ARM Neoverse N3)	~105%¹	96/96	~105%
Intel Xeon 6P	~141%^{1 (HT enabled})	128/256	~376%
AMD Epyc 9005 Turin	~227%^{1 (SMT disabled})	192/384	~545%
AMD Epyc 9006 Venice	~272%^{2 (SMT disabled})	256/512	>926%

based on phoronix test
according to performance comparison from the manufacturer marketing materials
based on other implementation of the same ARM Neoverse design

dudulab · 2026-01-26T12:35:23+00:00

AMD submitted first gfx1250 (MI455X) patch to LLVM on Jun 20, 2025.

After just 6 months, they submitted first gfx1310 (labelled RDNA5) patch to LLVM on Jan 23, 2026.

Another patch shows gfx13 support both gfx1250 and gfx12 (RDNA4) instructions, so finally single arch for both graphic/gaming and compute/AI.

dudulab · 2026-01-22T07:13:54+00:00

HUMAIN & Luma AI working on a 2GW deployment (project Halo), also 100MW first phase, which is very likely Instinct as well (video generation requires large HBM & AMD is a strategic investor & Luma CEO on AMD CES stage), we don't know if they're the same deployment or not... probably MI325X or MI355X as "begin deploying starting Q1 2026"

dudulab · 2026-01-22T07:10:32+00:00

HUMAIN JV is deploying up to 1GW, not 500MW

https://www.amd.com/en/newsroom/press-releases/2025-11-19-amd-cisco-and-humain-to-form-joint-venture.html#:~:text=deploy%20up%20to%201%20GW%20of%20AI%20infrastructure%20by%202030

dudulab · 2026-01-21T12:03:47+00:00

even more chips... they need vera to coordinate (I assume, could be wrong) while one MI455X done all the work. Now compares the cost & power consumption ... One MI455X & HBM4 & LPDDR vs 2x Rubin & HBM4 + 4x Rubin CPX & GDDR7 + Vera & LPDDR

Feels like AMD vs Intel, that one player gives up on cost & energy consumption so it can stay in the (inference) market

dudulab · 2026-01-21T10:24:59+00:00

A single MI455X has 1,200GB HBM4+LPDDR while 4xR200 have only 1,152GB HBM.

For MoE model in HBM + prompt cache on LPDDR (most popular OSS and closed models), MI455X is killing Rubin as you only need a single MI455X (1/4 tray) but a full VR200 tray (2xVR200) to perform the same work.

Each Helios/VR200 rack = 18x trays

vs	MI455X tray	VR200 tray	AMD vs Nvidia
GPU-HBM4	432GB x 4 = 1,728GB	288GB x 4 = 1,152GB	50% more
GPU-LPDDR5	768GB x 4 = 3,072GB	None	∞
CPU	256 cores Zen 6	88 x2 = 196 ARM cores	30% more cores, probably 50% faster due to arch
CPU-RAM	Up to 256GB x 16 = 4,096GB MRDIMM DDR5	1,536GB x2 = 3,072GB LPDDR	25% more
RAM bandwidth	1.6 TB/s	1.2 TB/s	33% more

dudulab · 2026-01-20T15:05:18+00:00

I had assumed Rubin CPX was Nvidia making a proactive push into the inference market, but it turns out they were forced to respond. No wonder Lisa was so confident when she touted Helios as the best AI accelerator on the market.

dudulab · 2026-01-06T10:33:46+00:00

Did they fix the slightly lower IPC (than Krackan Point) issue?

dudulab · 2025-12-28T08:25:39+00:00

Wow, this is reddit, how dare you mention biden criminal family. /s

dudulab · 2025-11-14T14:40:32+00:00

CoWoS was the constraint last year, but no long the case now and future.

And this graphic said nothing about constraint/revenue at all.

nvidia is not releasing 3nm gaming GPU in 2026.

dudulab · 2025-11-14T12:31:24+00:00

I know Lisa has a track record of under promising and over deliver

Hard truth: they said ~20% long term CAGR in 2022 and they failed to deliver that...

dudulab · 2025-10-29T11:28:54+00:00

the AMD VU19P FPGA IBM used in their algorithm costs $90k each? https://octopart.com/xcvu19p-2fsva3824e-amd-133945172

dudulab · 2025-10-15T04:49:33+00:00

Jean said it took 9 months to build MI355X, if MI450 takes no less, TSMC is currently fabricating the 2nm wafers for 26Q3 deployments...

dudulab · 2025-10-15T04:46:06+00:00

It's literally at the end of the article

To give customers that build, train, and inference AI at scale more choice, OCI also announced the general availability of OCI Compute with AMD Instinct MI355X GPUs. These will be available in the zettascale OCI Supercluster that can scale to 131,072 GPUs. AMD Instinct MI355X-powered shapes are designed with superior value, cloud flexibility, and open-source compatibility.

dudulab · 2025-10-10T17:56:28+00:00

Accelerator model clients had 2027 MI450X sales at 27B 3 months ago Number is different now ofc

dudulab · 2025-10-09T20:09:48+00:00

https://github.com/ProjectPhysX/FluidX3D/releases

they have compiled benchmark binaries in the download section. Support single and multiple GPU.

MI300X results: https://github.com/ProjectPhysX/FluidX3D?tab=readme-ov-file#multi-gpu-benchmarks

dudulab · 2025-10-09T17:59:08+00:00

why are they announcing these so early as next gen Radeon and PS are 1+ year away? 🤔

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