> Why aren’t these AI companies submitting to the TOP500 to show off their computing prowess?
my knowledge is 10+ years out of date, but once upon a time if they'd chosen to, Google could have had _several_ entries in the top 10 of the TOP500 list
It's just poker, they didn't want to tip their hand
Even before AI training clusters became important, Google has had an outstanding custom fabric (there's papers about it) together with the ability to tune NICs for their own cases, and "their own cases" meant nearly everything engineered within Google. Ethernet hardware has had low kernel latency and DMA for a long time; it's the rest of the stack that hurts. But as far back as the early 2010s (if not further back, that goes beyond my knowledge horizon), you could just make it not hurt, if you had the software engineers to do it.
Historically there have been a bunch of clusters on the Top 500 that weren't used for HPC. The tell is that they used Ethernet (this was before RoCE). It's less efficient but you can still get an OK Linpack score.
TOP500 hasn't been a particularly useful measure of practical computing power in modern systems for many years because what it measures isn't a significant bottleneck in most real systems. It has become a measure of how much money someone is willing to spend for bragging rights. (HPCG is better in that it is a bit more bandwidth focused but still pretty narrow.)
Most companies with huge systems don't participate.
I wonder if there would have been an opportunity to generate some finer-grained benchmarks with something like BiCGStab+ILU (or maybe CG+incomplete cholesky). Instead of CG+Gauss Seidel. The pitch being, you might have made different memory vs compute trade-offs with designing your cluster, but you should be able to select a fill-in factor for the preconditioner to suit it.
> We think it is highly likely that these LX2 chiplets are etched using SMIC 7 nanometer processes at the N+3 refinement, and we base that on the fact that the chip only runs at 1.55 GHz. That is nowhere near the 3 GHz that SMIC can push with that process, but it is probably lower to get the memory and core speeds more balanced. [1]
It is likely that those cores are dedicated to unrelated management, monitoring, and administrative tasks. This is common and many workloads are throttled on bandwidth anyway. For the purposes of the benchmark, those cores are not participating in the workload.
TOP500 can be done with inexpensive silicon. It is more about a willingness to aggregate enough hardware in one place. As a benchmark, it tells you almost nothing about computing power or scalability for other applications because it doesn't exercise the bottlenecks most high-scale applications have.
We're too busy regulating the tech, not granting access to US engineers and companies, arguing against power and data centers, stopping skilled immigration.
This is absolutely going to bite us in the face in five to ten years.
Separate issue that has nothing to do with US manufacturing or HPC. I think our retreat from science funding and offshoring advanced manufacturing is a bigger issue.
my knowledge is 10+ years out of date, but once upon a time if they'd chosen to, Google could have had _several_ entries in the top 10 of the TOP500 list
It's just poker, they didn't want to tip their hand
(These are the systems to which GP was referring at Google.)
I know Google wants to compare their stuff to El Capitan or whatever but the comparison does not seem valid to me.
Most companies with huge systems don't participate.
Based on the ARMv9.2.
[1] https://www.nextplatform.com/hpc/2026/06/25/a-deep-dive-on-c...
I’m sure there is a good reason for this, which is..?
This is absolutely going to bite us in the face in five to ten years.