4 ms·

Totally agree with your last point. But based on my understanding, over the past 5-ish years commodity multicores with multi-terabyte memories have made a big d

by moab 4y ago

Totally agree with your last point. But based on my understanding, over the past 5-ish years commodity multicores with multi-terabyte memories have made a big dent in the supremacy of supercomputing, at least for some of the topics you mention (thinking about graph analysis in particular).

jandrewrogers 4y ago
Graph analysis was one of my core research areas in my supercomputing days. You can do it on commodity hardware with some caveats. This problem is intrinsically cache-unfriendly, which makes it interesting but also slow even when it fits in memory on a single machine. We made a lot of progress on approaching the theoretical throughput bound on real hardware and even made it work reasonably well when storage-backed, with some caveats. That said, multi-terabyte memories won’t solve interesting problems; we already had that. When I was working on this 15-ish years ago, the real-world data models had trillions of vertices, never mind edges. And that has only gotten larger with time. A lot of the research ended up focusing on the problem of how do you boil the ocean selectively and incrementally to optimize throughput. There is no way to trivially throw hardware at the problem; graph-cutting is hard, and you have to do it even within single servers. Even with sophisticated latency-hiding, it ends up being about effective bandwidth in a context where caches are almost useless. For graph analysis specifically, we could do a lot with big servers, this is true. But it would require a completely different software architecture to the way most graph analysis is done now. This is perpetually on my “copious spare time” lists of projects because there is a big gap here.
- moab 4y ago
  Makes sense. I hope you keep working on this. There is a big gap between what people are doing in the academic (and even publicly-described industrial literature) and what you describe. So I think there is a lot of opportunity to push on this front if you have some ideas.
dekhn 4y ago
every time a commodity multicore machine gets better, the supercomputer folks just switch to a larger problem that wouldn't fit on a single machine. Their goal is to engineer a system/build a code that reaches peak performance limited primarily by the physical constraints of the biggest systems.

by moab 4y ago

jandrewrogers 4y ago

Graph analysis was one of my core research areas in my supercomputing days. You can do it on commodity hardware with some caveats. This problem is intrinsically cache-unfriendly, which makes it interesting but also slow even when it fits in memory on a single machine. We made a lot of progress on approaching the theoretical throughput bound on real hardware and even made it work reasonably well when storage-backed, with some caveats. That said, multi-terabyte memories won’t solve interesting problems; we already had that. When I was working on this 15-ish years ago, the real-world data models had trillions of vertices, never mind edges. And that has only gotten larger with time. A lot of the research ended up focusing on the problem of how do you boil the ocean selectively and incrementally to optimize throughput. There is no way to trivially throw hardware at the problem; graph-cutting is hard, and you have to do it even within single servers. Even with sophisticated latency-hiding, it ends up being about effective bandwidth in a context where caches are almost useless. For graph analysis specifically, we could do a lot with big servers, this is true. But it would require a completely different software architecture to the way most graph analysis is done now. This is perpetually on my “copious spare time” lists of projects because there is a big gap here.

moab 4y ago
Makes sense. I hope you keep working on this. There is a big gap between what people are doing in the academic (and even publicly-described industrial literature) and what you describe. So I think there is a lot of opportunity to push on this front if you have some ideas.

dekhn 4y ago

every time a commodity multicore machine gets better, the supercomputer folks just switch to a larger problem that wouldn't fit on a single machine. Their goal is to engineer a system/build a code that reaches peak performance limited primarily by the physical constraints of the biggest systems.