Good points! Overall efficiency improvements in hybrid CPU+Accelerator architectures may hinge on whether some type of RISC-vs-CISC duality can be identified also in mixed-precision matrix-vector units. This could be key to bringing us closer to the Zettascale, as Kathy Yelick will discuss in her ISC 2024 Keynote ( https://www.isc-hpc.com/conference-keynote-2024.html ).

Scaling Frontier straight to 1.2 ZF/s would see it consume 23 GW of juice. Assuming that MxP is acceptable for FP64 accuracy and gives a 10x performance boost reduces that to 2.3 GW — which is already less than Microsoft’s 5 GW “death”-star-gate AI project ( https://www.nextplatform.com/2024/04/01/microsoft-stargate-the-next-ai-platform-will-be-an-entire-cloud-region/ , https://www.theregister.com/2024/04/01/microsoft_openai_5gw_dc/ ). Switching to RISC-CPU and RISC-accelerator (if possible) might get this down to 1 GW– still large, but 30 years ago (June 1994) the Top500 #1 was Sandia’s XP/S140 at just 184 kW (and 0.14 PF/s). If it was acceptable to increase power consumption by 100x to get from there to the ExaFlop of Frontier, maybe it is okay to increase it another 50x for a FP64 MxP ZettaFlopper?

Thanks for the correction. I see it now: Green500 #79 Leonardo-CPU ( https://top500.org/lists/green500/list/2023/11/ ), right there with Mare Nostrum 5 GPP, Snellius Phase 2 CPU, Shaheen III – CPU, … I’m glad I had it wrong (it puts my mind back at ease to see this 2x-3x better efficiency for A64FX ARM in CPU-only action, as actually expected. The universe is back in harmony!).

Hmmmm … no, and yes! The MN-3 is accelerated by custom MN-core processors as you can see here: https://projects.preferred.jp/supercomputers/en/ — it is not a CPU-only system and so A64FX wins on perf/Watt in that category at 16 GF/W. The first x86-only looks to be Leonardo at 7 GF/W (Crossroads is near 5 GF/W).

But yes, the Ballroom blitz Battle Royale between the swashbuckling stronger swagger of El Capitan, Santa’s red-nosed rocket sleigh, the Swiss-cheese-grater of the Alps, and this new EXA1 atomic leaping frog, should be most entertaining (not to mention the recently awakened sleeping beauty!)! q^8

Hopefully that all takes place next month, hosted by the delicious Hamburgers of HPC gastronomy! (May 12-16: https://www.isc-hpc.com/ )

Comparing performance and efficiency of LANL’s Crossroads (CPU-only) to that of Venado’s Grace-Grace partition, and also that of MI300A-based systems (El Capitan) to Grace-Hopper machines (Venado, Alps, CEA EXA1 HE, …) should be most informative in this, IMHO. Maybe we’ll see more power-sipping accelerators from ARM (beyond the 4-TOPs U85)?

The cheap money/easy funding of the past decade got us business models like Uber and Door dash with a lot of contenders and little (or negative) margin desperate to turn spending and market share into margin and profit. It didn’t work well for most of them unless they sold their shop early enough.

AI and especially the GenAI seems a lot like it. Except this time the biggest players are the ones most able to drop 9-13 figures and the least likely to make money by being acquired and/or going public for the first time.

There’s a lot of money to be made with AI, but I’m not convinced it’s in the flagship Geminis, Copilots, Llamas and MM1s of this world. I see a lot more revenue from engineering and science applications, like Synopsis seems to think of with Ansys, or internal models to manage systems/networks and that sort of applications. But that’s not as flashy or impressive for the public and boards to drop money on due to FOMO.