On 2015-09-22 19:16, Andi Kleen wrote:
I really like this idea, as it both makes getting random numbers on busy servers faster, and makes replay attacks more difficult.From: Andi Kleen <a...@linux.intel.com>We had a case where a 4 socket system spent >80% of its total CPU time contending on the global urandom nonblocking pool spinlock. While the application could probably have used an own PRNG, it may have valid reasons to use the best possible key for different session keys. The application still ran acceptable under 2S, but just fell over the locking cliff on 4S. Implementation ============== The non blocking pool is used widely these days, from every execve() (to set up AT_RANDOM for ld.so randomization), to getrandom(3) and to frequent /dev/urandom users in user space. Clearly having such a popular resource under a global lock is bad thing. This patch changes the random driver to use distributed per NUMA node nonblocking pools. The basic structure is not changed: entropy is first fed into the input pool and later from there distributed round-robin into the blocking and non blocking pools. This patch extends this to use an dedicated non blocking pool for each node, and distribute evenly from the input pool into these distributed pools, in addition to the blocking pool. Then every urandom/getrandom user fetches data from its node local pool. At boot time when users may be still waiting for the non blocking pool initialization we use the node 0 non blocking pool, to avoid the need for different wake up queues. For single node systems (like the vast majority of non server systems) nothing changes. There is still only a single non blocking pool. The different per-node pools also start with different start states and diverge more and more over time, as they get feed different input data. So "replay" attacks are difficult after some time.
I agree that this is acceptable, it wouldn't be hard for someone who wants to to just modify the script to set it's own task affinity and loop through the nodes (although that might get confusing with hot-plugged/hot-removed nodes).Without hardware random number seed support the start states (until enough real entropy is collected) are not very random, but that's not worse than before Since we still have a global input pool there are no problems with load balancing entropy data between nodes. Any node that never runs any interrupts would still get the same amount of entropy as other nodes. Entropy is fed preferably to nodes that need it more using the existing 75% threshold. For saving/restoring /dev/urandom, there is currently no mechanism to access the non local node pool (short of setting task affinity). This implies that currently the standard init/exit random save/restore scripts would only save node 0. On restore all pools are updates. So the entropy of non 0 gets lost over reboot. That seems acceptable to me for now (fixing this would need a new separate save/restore interface)
I'd almost say that making the partitioning level configurable at build time might be useful. I can see possible value to being able to at least partition down to physical cores (so, shared between HyperThreads on Intel processors, and between Compute Module cores on AMD processors), as that could potentially help people running large numbers of simulations in parallel.Scalability =========== I tested the patch with a simple will-it-scale test banging on get_random() in parallel on more and more CPUs. Of course that is not a realistic scenario, as real programs should do some work between getting random numbers. But it's a worst case for the random scalability. On a 4S Xeon v3 system _without_ the patchkit the benchmark maxes out when using all the threads on one node. After that it quickly settles to about half the throughput of one node with 2-4 nodes. (all throughput factors, bigger is better) Without patchkit: 1 node: 1x 2 nodes: 0.75x 3 nodes: 0.55x 4 nodes: 0.42x With the patchkit applied: 1 node: 1x 2 nodes: 2x 3 nodes: 3.4x 4 nodes: 6x So it's not quite linear scalability, but 6x maximum throughput is already a lot better. A node can still have a large number of CPUs: on my test system 36 logical software threads (18C * 2T). In principle it may make sense to split it up further. Per logical CPU would be clearly overkill. But that would also add more pressure on the input pools. For now per node seems like a acceptable compromise.
Personally, I'm the type who would be willing to take the performance hit to do it per logical CPU just for the fact that it would make replay attacks more difficult, but I'm probably part of a very small minority in that case.
/dev/random still uses a single global lock. For now that seems acceptable as it normally cannot be used for real high volume accesses anyways. The input pool also still uses a global lock. The existing per CPU fast pool and "give up when busy" mechanism seems to scale well enough even on larger systems.
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