There is a phenomenon where as you get older, your sense of scale becomes somewhat fixed in the earlier era that shaped you– things like expecting the Dollar Store to carry items for 1$, or to get a burger and fries for less than twenty bucks– or, in this case, thinking of supercomputers as being petaflop-scale machines. That’s not wrong, per se– most of the world’s fastest machines benchmarks are best measured in petaflops– but when you’re clocking at 2198 of the things, it becomes easier just to say that the LineShine computer can do 2.188 exaflops. At double precision. With CPUs only. Yes, we are impressed.
Even more impressive is that this machine just debuted in China, which means it was built without the benefit of the latest-and-greatest Western chips, thanks to US sanctions. It’s using a made-in-China LX2 CPU with 304 ARMv9 cores onboard. Well, it’s actually using around 46 thousand of them, but who’s counting?
Each CPU actually consists of two separate compute dies and onboard high bandwith memory (HBM) and DRAM– 4GB of HBM and 32GB of DDR5. The 152 ARMv9 CPU cores on each chip are all built with Scalable Vector Extensions (SVE) and Scalable Matrix Extensions (SME), so despite the lack of GPUs LineShine will have no problem doing the sorts of vector processing that is traditional for high-performance computing, given the 13.79 million cores.
On the other hand, the lack of GPUs shows when you change benchmarks– LineShine is number one in the rankings for High Performance Linpack (HPL), but getting outside the 64-bit box, the supercomputer only hits number four on the HPL-MxP mixed-precision benchmark, behind machines that pair their CPUs with accelerators like GPUs or NPUs. That may mollify the American ego, as while their El Capitain was bumped to second place on the HPL list, they can still claim the pole position on HPL-MxP. Which computer is actually more capable depends entirely on what you want to do with it, and neither Lawrence Livermore National Laboratory nor China’s National Supercomputing Centre in Shenzhen advertise their compute queues, though this paper suggests at least one job will be crunching earth observation data.
The definition of a supercomputer has shifted over time, and it’s only a matter of time before LineShine and El Capitain end up on the auction block, like other supercomputers before them. We might question it when it comes to desktops, but for institutional HPC, no amount of computing ever seems to be enough.
