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by almostgotcaught 579 days ago
> where you use up to a whole machine

i mean rick stevens et al can grab all of polaris too but even so - it's just a bunch of nodes and you're responsible for distributing your work across those nodes efficiently. there's no sense in which it's a "single computer" in any way, shape or form.

1 comments

The same way that you're responsible for distributing your single threaded code between cores on your desktop.
No. Threads run typically in the same address space. HPC processes on different nodes typically do not.
Define address space.

Cache is not shared between cores.

HPCs just have more levels of cache.

Lest you ignore the fact that infiniband is pretty much on par with top of the line ddr speeds for the matching generation.

>Lest you ignore the fact that infiniband is pretty much on par with top of the line ddr speeds for the matching generation.

You can't go faster than the speed of light (yet) and traveling a few micrometers will always be much faster than traversing a room (plus routing and switching).

Many HPC tasks nowadays are memory-bound rather than CPU-bound, memory-latency-and-throughput-bound to be more precise. An actual supercomputer would be something like the Cerebras chip, a lot of the performance increase you get is due to having everything on-chip at a given time.

There are four sentences in your comment.

None of them logically relate to another.

One is a question.

And the rest are wrong.

Really? How about: "This pointer is valid, has the same numeric value (address) and points to the same data in all threads". The point is not the latency nor bandwidth. The point is the programming/memory model. Infiniband maybe makes multiprocessing across nodes as fast as multiprocessing on a single node. But it's not multithreading.
>Cache is not shared between cores.

I feel sorry for you if you believe this. It's not true physically nor is it true on the level of the cache coherence protocol nor is it true from the perspective of the operating system.

Tell me you've never run a distributed workload without telling me. You realize if what you were saying were true, HPC would be trivial. In fact it takes a whole lot of PhDs to manage the added complexity because it's not just a "single computer".
If you think parallelizing single threaded code is trivial ... well there's nothing else to say really.
Is there like a training program available for learning how to be this obstinate? I would love to attend so that I can win fights with my wife.
Maybe llm_trw is your wife?