>Sequential throughput: ~1.3 GB/s
[on a RTX 3070 Laptop]
This RTX 3070 chip is on PCIe 4.0 x16 which should give 64GB/s. The 8GB of GDDR6 is 448GB/s.
Swapping to an NVMe drive would be twice as fast, but with higher latency.
>Sequential throughput: ~1.3 GB/s
[on a RTX 3070 Laptop]
This RTX 3070 chip is on PCIe 4.0 x16 which should give 64GB/s. The 8GB of GDDR6 is 448GB/s.
Swapping to an NVMe drive would be twice as fast, but with higher latency.
Edit: Their benchmarks are also run using ZRAM, which compresses pages before writing to swap. Not sure what the performance overhead of that is, but it's probably quite a bit.
First of all, it's a userspace program hooking the nbd driver, which is known for being slow. It also uses a bounce buffer in userspace before transferring to the GPU. So when the kernel needs to swap a page, it has to first copy it into a userspace facing buffer. The userspace program that has to wake back up and issue the cuda operation to copy the page into device memory.
nbd also doesn't really do a good job of supporting high queue depth or merging adjacent accesses. So if the kernel is issuing a bunch of 4K page swaps without any coalescing, you're going to end up with at least million kernel/userspace context switches per second just to handle 4 GB/s (4 GB / 4K page), let alone 64 GB/s. And that's just the NBD portion, forget the mess that is the NVIDIA driver. PCIe can move a lot of data, but in order to get anything even resembling the full bandwidth, you have to have use DMA engines with long page lists. Having to set up a transfer for every 4K page over PCIe will not reach full saturation of the bus.
Swapping to NVMe is a very optimized path -> the swapper can submit lists of pages directly to the NVMe driver and the controller can DMA them directly out of RAM, no copies or context switches CPU side at all.
This could probably be improved by migrating to the ublk driver as it might let you avoid the userspace bounce buffer. It'd also be able to have multiple write queues to at least set up CUDA copies in parallel.
one can get rid of zram and just reimplement some compression in shaders but I think that would be a pointless optimization.
Even if the swap system overhead drops to just a data copy, the memory management layer prevents swap from scaling to higher bandwidths. The issue is not data movement; it is in the page unmapping step (which requires expensive TLB shootdowns). Larger kernel changes are required.
My group wrote a paper on this: https://dl.acm.org/doi/10.1145/3731569.3764842
Linux's swap system is undergoing some large refactors lately. Hopefully some insights either from our work or Hermit (NSDI '23) can make it in to the mainline. I think Hermit's `rmap` optimization in particular is a candidate for upstream use.
RAM/VRAM don’t degrade from use.
but flash endurance isn't a strong argument here. you probably have O(TB) of flash, and aren't going to produce PB of swap writes any time soon. if you do a lot of swapping to a small flash device, it'll happen sooner.
I'm typing from a quite old 4GB laptop, which swaps heavily to a 250G SATA ssd. sure, it's not great, but it also costs zero. currently 9GB of swap is used, and it's not really noticeable. if I open 20 more tabs, it can introduce pauses.
google says this drive was released in 2014, and SMART says POH is about 10 years.
SMART also says wear leveling count is 665 and total written is 165327189538 LBAs (78834 GiB, or 338 drive-writes). I'm not expecting it to die soon, though using a 4G laptop is a bit of a stunt these days...
the point is that a system that has sustained heavy swapping for years has not generates so many writes to worry much. a modern system with 10x speed and 10x capacity (and probably less RAM deficit) would have even less effect. even for QDR with it's few-hundred cycle endurance spec...
All of this is to say that, it does have a potential impact on flash, if you rebuild often, which tends to happen on Gentoo.