On Sun, Jun 14, 2020 at 4:45 PM Kanthi P <Pavuluri.email@example.com> wrote:
[Edited Message Follows]
Thanks Song and Andrii for the response.
Use-case is global rate-limiting for incoming TCP connections. And we want to implement the token bucket algorithm using XDP for this purpose.
So we are planning to have a map that holds a token counter which gets two kinds of updates:
1. Periodic increments with 'x' number of tokens per second
2. Decrements as and when we get a new TCP connection request.
Most of our systems are 64 core machines. Since every core would try to update the counter in parallel as the packets arrive each of them, the problem I am imagining is that I might miss few updates of the counter as one core update can overwrite other’s.
I guess it is still ok to lose the case 2 type of updates as that might just allow a small fraction of more or less connections than what is configured.
But I cannot afford to lose case 1 kind of updates as that could mean that I cannot process bunch of connections until the next second.
So if I use "__sync_fetch_and_add" for incrementing the counter (for case 1), would it guarantee that this update is never missed(though some other core is trying to update the map to decrement the counter to account the incoming connection at the same time)?
You should use __sync_fetch_and_add() for both cases, and then yes,
you won't lose any update. You probably would want
__sync_add_and_fetch() to get the counter after update, but that's not
supported by BPF yet. But you should still get far enough with
Also, if you could use BPF global variables instead of BPF maps
directly, you will avoid map lookup overhead on BPF side. See BPF
selftests for examples, global vars are being used quite extensively
BTW, you mentioned that you are going to update counter on every
packet, right? On 64-core machine, even __sync_fetch_and_add() might
be too much overhead. I recommend looking at Paul McKenney's book
(), see chapter on counting. It might provide you with good ideas
how to scale this further to per-CPU counters, if need be.
My understanding is that __sync_fetch_and_add translates to BPF_XADD internally. And it looks like spin locks are being supported from 5.x kernel versions, we are on lower version, so can’t try this one atm.
P.S there has been some problem sending the reply, which resulted in multiple edits and deletes, please bear with me
On Wed, May 27, 2020 at 1:29 AM Andrii Nakryiko <firstname.lastname@example.org> wrote:
On Fri, May 22, 2020 at 1:07 PM Kanthi P <Pavuluri.email@example.com> wrote:
Stating that spin locks are costly without empirical data seems
I’ve been reading that hash map’s update element is atomic and also that we can use BPF_XADD to make the entire map update atomically.
But I think that doesn’t guarantee that these updates are thread safe, meaning one cpu core can overwrite other core’s update.
Is there a clean way of keeping them thread safe. Unfortunately I can’t use per-cpu maps as I need global counters.
And spin locks sounds a costly operation. Can you please throw some light?
premature. What's the scenario? What's the number of CPUs? What's the
level of contention? Under light contention, spin locks in practice
would be almost as fast as atomic increments. Under heavy contention,
spin locks would probably be even better than atomics because they
will not waste as much CPU, as a typical atomic retry loop would.
But basically, depending on your use case (which you should probably
describe to get a better answer), you can either:
- do atomic increment/decrement if you need to update a counter (see
examples in kernel selftests using __sync_fetch_and_add);
- use map with bpf_spin_lock (there are also examples in selftests).