| Message ID | ebf0fac84cb1d19bdc6e73576e3cc40a9cab0635.1711649501.git.kjlx@templeofstupid.com (mailing list archive) |
|---|---|
| State | New, archived |
| Headers | show |
| Series | KVM: arm64: Limit stage2_apply_range() batch size to smallest block | expand |
Hi Krister, On Thu, Mar 28, 2024 at 12:05:08PM -0700, Krister Johansen wrote: > stage2_apply_range() for unmap operations can interfere with the > performance of IO if the device's interrupts share the CPU where the > unmap operation is occurring. commit 5994bc9e05c2 ("KVM: arm64: Limit > stage2_apply_range() batch size to largest block") improved this. Prior > to that commit, workloads that were unfortunate enough to have their IO > interrupts pinned to the same CPU as the unmap operation would observe a > complete stall. With the switch to using the largest block size, it is > possible for IO to make progress, albeit at a reduced speed. Can you describe the workload a bit more? I'm having a hard time understanding how you're unmapping that much memory on the fly in your workload. Is guest memory getting swapped? Are VMs being torn down? Also, it seems a bit odd to steer interrupts *into* the workload you care about... > Further reducing the stage2_apply_range() batch size has substantial > performance improvements for IO that share a CPU performing an unmap > operation. By switching to a 2mb chunk, IO performance regressions were > no longer observed in this author's tests. E.g. it was possible to > obtain the advertised device throughput despite an unmap operation > occurring on the CPU where the interrupt was running. There is a > tradeoff, however. No changes were observed in per-operation timings > when running the kvm_pagetable_test without an interrupt load. However, > with a 64gb VM, 1 vcpu, and 4k pages and a IO load, map times increased > by about 15% and unmap times increased by about 58%. In essence, this > trades slower map/unmap times for improved IO throughput. There are other users of the range-based operations, like write-protection. Live migration is especially sensitive to the latency of page table updates as it can affect the VMM's ability to converge with the guest. > Cc: <stable@vger.kernel.org> # 5.15.x: 3b5c082bbfa2: KVM: arm64: Work out supported block level at compile time > Cc: <stable@vger.kernel.org> # 5.15.x: 5994bc9e05c2: KVM: arm64: Limit stage2_apply_range() batch size to largest block > Cc: <stable@vger.kernel.org> # 5.15.x This is a performance improvement, *not* a correctness fix. Please don't cc stable for it. > Suggested-by: Ali Saidi <alisaidi@amazon.com> > Signed-off-by: Krister Johansen <kjlx@templeofstupid.com> > --- > arch/arm64/include/asm/kvm_pgtable.h | 4 ++++ > arch/arm64/kvm/mmu.c | 2 +- > 2 files changed, 5 insertions(+), 1 deletion(-) > > diff --git a/arch/arm64/include/asm/kvm_pgtable.h b/arch/arm64/include/asm/kvm_pgtable.h > index 19278dfe7978..b0c4651a4d9a 100644 > --- a/arch/arm64/include/asm/kvm_pgtable.h > +++ b/arch/arm64/include/asm/kvm_pgtable.h > @@ -19,11 +19,15 @@ > * - 4K (level 1): 1GB > * - 16K (level 2): 32MB > * - 64K (level 2): 512MB > + * > + * The max block level is the _smallest_ supported block size for KVM. This feels like a non sequitur given the old comment is left in place... > */ > #ifdef CONFIG_ARM64_4K_PAGES > #define KVM_PGTABLE_MIN_BLOCK_LEVEL 1 > +#define KVM_PGTABLE_MAX_BLOCK_LEVEL 2 > #else > #define KVM_PGTABLE_MIN_BLOCK_LEVEL 2 > +#define KVM_PGTABLE_MAX_BLOCK_LEVEL KVM_PGTABLE_MIN_BLOCK_LEVEL > #endif > > #define kvm_lpa2_is_enabled() system_supports_lpa2() > diff --git a/arch/arm64/kvm/mmu.c b/arch/arm64/kvm/mmu.c > index dc04bc767865..1e927b306aee 100644 > --- a/arch/arm64/kvm/mmu.c > +++ b/arch/arm64/kvm/mmu.c > @@ -41,7 +41,7 @@ static phys_addr_t __stage2_range_addr_end(phys_addr_t addr, phys_addr_t end, > > static phys_addr_t stage2_range_addr_end(phys_addr_t addr, phys_addr_t end) > { > - phys_addr_t size = kvm_granule_size(KVM_PGTABLE_MIN_BLOCK_LEVEL); > + phys_addr_t size = kvm_granule_size(KVM_PGTABLE_MAX_BLOCK_LEVEL); > > return __stage2_range_addr_end(addr, end, size); > } This doesn't feel right to me. A property that we had before is that leaf entries are visited at most once, since every mapping size was evenly divisible into KVM_PGTABLE_MIN_BLOCK_LEVEL. Seems like we could wind up visiting a PUD mapping 512 times, at least for 4K pages.
Hi Oliver, Thanks for the response. On Fri, Mar 29, 2024 at 06:48:38AM -0700, Oliver Upton wrote: > On Thu, Mar 28, 2024 at 12:05:08PM -0700, Krister Johansen wrote: > > stage2_apply_range() for unmap operations can interfere with the > > performance of IO if the device's interrupts share the CPU where the > > unmap operation is occurring. commit 5994bc9e05c2 ("KVM: arm64: Limit > > stage2_apply_range() batch size to largest block") improved this. Prior > > to that commit, workloads that were unfortunate enough to have their IO > > interrupts pinned to the same CPU as the unmap operation would observe a > > complete stall. With the switch to using the largest block size, it is > > possible for IO to make progress, albeit at a reduced speed. > > Can you describe the workload a bit more? I'm having a hard time > understanding how you're unmapping that much memory on the fly in > your workload. Is guest memory getting swapped? Are VMs being torn > down? Sorry I wasn't clear here. Yes, it's the VMs getting torn down that's causing the problems. The container VMs don't have long lifetimes, but some may be up to 256Gb in size, depending on the user. The workloads running the VMs aren't especially performance sensitive, but their users do notice when network connections time-out. IOW, if the performance is bad enough to temporarily prevent new TCP connections from being established or requests / responses being recieved in a timely fashion, we'll hear about it. Users deploy their services a lot, so there's a lot of container vm churn. (Really it's automation redeploying the services on behalf of the users in response to new commits to their repos...) > Also, it seems a bit odd to steer interrupts *into* the workload you > care about... Ah, that was only intentionally done for the purposes of measuring the impact. That's not done on purpose in production. Nevertheless, the example we tend to run into is that a box may have 2 NICs and each NIC has 32 Tx-Rx queues. This means we've got 64 NIC interrupts, each assigned to a different CPU. Our systems have 64 CPUs. What happens in practice is that a VM will get torn down, and that has a 1-in-64 chance of impacting the performance of the subset of the flows that are mapped via RSS to the interrupt that happens to be assigned to the CPU where the VM is being torn down. Of course, the obvious next question is why not just bind the VMs flows to the CPUs the VM is running on? We don't have a 1:1 mapping of network device to VM, or VM to CPU right now, which frustrates this approach. > > Further reducing the stage2_apply_range() batch size has substantial > > performance improvements for IO that share a CPU performing an unmap > > operation. By switching to a 2mb chunk, IO performance regressions were > > no longer observed in this author's tests. E.g. it was possible to > > obtain the advertised device throughput despite an unmap operation > > occurring on the CPU where the interrupt was running. There is a > > tradeoff, however. No changes were observed in per-operation timings > > when running the kvm_pagetable_test without an interrupt load. However, > > with a 64gb VM, 1 vcpu, and 4k pages and a IO load, map times increased > > by about 15% and unmap times increased by about 58%. In essence, this > > trades slower map/unmap times for improved IO throughput. > > There are other users of the range-based operations, like > write-protection. Live migration is especially sensitive to the latency > of page table updates as it can affect the VMM's ability to converge > with the guest. To be clear, the reduction in performance was observed when I concurrently executed both the kvm_pagetable_test and a networking benchmark where the NIC's interrupts were assigned to the same CPU where the pagetable test was executing. I didn't see a slowdown just running the pagetable test. > > Cc: <stable@vger.kernel.org> # 5.15.x: 3b5c082bbfa2: KVM: arm64: Work out supported block level at compile time > > Cc: <stable@vger.kernel.org> # 5.15.x: 5994bc9e05c2: KVM: arm64: Limit stage2_apply_range() batch size to largest block > > Cc: <stable@vger.kernel.org> # 5.15.x > > This is a performance improvement, *not* a correctness fix. Please don't > cc stable for it. Apologies. I consulted the Stable Rules[1] before applying these tags and the guidance it gave was just that "It must either fix a real bug that bothers people." In our case, the teardown causes TCP throughput to drop from 9.5Gbps to about 2Gbps during a teardown, which is something that does bother our users. > > --- > > arch/arm64/include/asm/kvm_pgtable.h | 4 ++++ > > arch/arm64/kvm/mmu.c | 2 +- > > 2 files changed, 5 insertions(+), 1 deletion(-) > > > > diff --git a/arch/arm64/include/asm/kvm_pgtable.h b/arch/arm64/include/asm/kvm_pgtable.h > > index 19278dfe7978..b0c4651a4d9a 100644 > > --- a/arch/arm64/include/asm/kvm_pgtable.h > > +++ b/arch/arm64/include/asm/kvm_pgtable.h > > @@ -19,11 +19,15 @@ > > * - 4K (level 1): 1GB > > * - 16K (level 2): 32MB > > * - 64K (level 2): 512MB > > + * > > + * The max block level is the _smallest_ supported block size for KVM. > > This feels like a non sequitur given the old comment is left in place... I'll fix if we keep this approach. Is the objection to the name KVM_PGTABLE_MAX_BLOCK_LEVEL or just the comment? > > */ > > #ifdef CONFIG_ARM64_4K_PAGES > > #define KVM_PGTABLE_MIN_BLOCK_LEVEL 1 > > +#define KVM_PGTABLE_MAX_BLOCK_LEVEL 2 > > #else > > #define KVM_PGTABLE_MIN_BLOCK_LEVEL 2 > > +#define KVM_PGTABLE_MAX_BLOCK_LEVEL KVM_PGTABLE_MIN_BLOCK_LEVEL > > #endif > > > > #define kvm_lpa2_is_enabled() system_supports_lpa2() > > diff --git a/arch/arm64/kvm/mmu.c b/arch/arm64/kvm/mmu.c > > index dc04bc767865..1e927b306aee 100644 > > --- a/arch/arm64/kvm/mmu.c > > +++ b/arch/arm64/kvm/mmu.c > > @@ -41,7 +41,7 @@ static phys_addr_t __stage2_range_addr_end(phys_addr_t addr, phys_addr_t end, > > > > static phys_addr_t stage2_range_addr_end(phys_addr_t addr, phys_addr_t end) > > { > > - phys_addr_t size = kvm_granule_size(KVM_PGTABLE_MIN_BLOCK_LEVEL); > > + phys_addr_t size = kvm_granule_size(KVM_PGTABLE_MAX_BLOCK_LEVEL); > > > > return __stage2_range_addr_end(addr, end, size); > > } > > This doesn't feel right to me. A property that we had before is that > leaf entries are visited at most once, since every mapping size was > evenly divisible into KVM_PGTABLE_MIN_BLOCK_LEVEL. > > Seems like we could wind up visiting a PUD mapping 512 times, at least > for 4K pages. I have an idea, but it seems to go against the current design of the pagtable walkers. My sense was that they've been written to discourage passing mutable state to the function that calls kvm_pgtable_walk(). If we were willing to permit this, it seems like we could leverage __kvm_pgtable_visit()'s knowledge about the size of the mapping it walked to determine whether range_addr_end should be incremented by our BLOCK_LEVEL constant, or advanced to the end of the mapping that was already successfully walked. (If I'm reading right, anyway) Does that seem like a reasonable approach? If we do modify the walk to allow state to be passed back, I have a second patch I'd like to send you. Ali found that there was a performance regression on the kvm_pagetable_test on the map creation step when a large number of threads operated on a comparatively small memory range. (E.g. 64 cpus and 8g of RAM). We debugged this a bit and found that there's an unmap in the map creation step if the test ends up instantiating a readable zero page that needs to be copied and made writable. With the deferred TLBI logic, the tlb invalidation happens at the end of the unmap operation whether a PTE is cleared or not. With so many threads, this doesn't always suceeed. The prior approach of just doing the invalidation in stage2_unmap_put_pte() outperforms the deferred invalidation, because stage2_unmap_put_pte() only calls __kvm_tlb_flush_vmid_ipa() if it clears a valid PTE. If we modify the walk to keep state on whether any PTEs are successfully cleared, and condition the deferred invalidation on that state, we obtain performance that is equivalent to the pre range based deferred invalidation approach. Thanks, -K
On Fri, 29 Mar 2024 19:15:37 +0000, Krister Johansen <kjlx@templeofstupid.com> wrote: > > Hi Oliver, > Thanks for the response. > > On Fri, Mar 29, 2024 at 06:48:38AM -0700, Oliver Upton wrote: > > On Thu, Mar 28, 2024 at 12:05:08PM -0700, Krister Johansen wrote: > > > stage2_apply_range() for unmap operations can interfere with the > > > performance of IO if the device's interrupts share the CPU where the > > > unmap operation is occurring. commit 5994bc9e05c2 ("KVM: arm64: Limit > > > stage2_apply_range() batch size to largest block") improved this. Prior > > > to that commit, workloads that were unfortunate enough to have their IO > > > interrupts pinned to the same CPU as the unmap operation would observe a > > > complete stall. With the switch to using the largest block size, it is > > > possible for IO to make progress, albeit at a reduced speed. > > > > Can you describe the workload a bit more? I'm having a hard time > > understanding how you're unmapping that much memory on the fly in > > your workload. Is guest memory getting swapped? Are VMs being torn > > down? > > Sorry I wasn't clear here. Yes, it's the VMs getting torn down that's > causing the problems. The container VMs don't have long lifetimes, but > some may be up to 256Gb in size, depending on the user. The workloads > running the VMs aren't especially performance sensitive, but their users > do notice when network connections time-out. IOW, if the performance is > bad enough to temporarily prevent new TCP connections from being > established or requests / responses being recieved in a timely fashion, > we'll hear about it. Users deploy their services a lot, so there's a > lot of container vm churn. (Really it's automation redeploying the > services on behalf of the users in response to new commits to their > repos...) I think this advocates for a teardown-specific code path rather than just relying on the usual S2 unmapping which is really designed for eviction. There are two things to consider here: - TLB invalidation: this should only take a single VMALLS12E1, rather than iterating over the PTs - Cache maintenance: this could be elided with FWB, or *optionally* elided if userspace buys in a "I don't need to see the memory of the guest after teardown" type of behaviour > > Also, it seems a bit odd to steer interrupts *into* the workload you > > care about... > > Ah, that was only intentionally done for the purposes of measuring the > impact. That's not done on purpose in production. > > Nevertheless, the example we tend to run into is that a box may have 2 > NICs and each NIC has 32 Tx-Rx queues. This means we've got 64 NIC > interrupts, each assigned to a different CPU. Our systems have 64 CPUs. > What happens in practice is that a VM will get torn down, and that has a > 1-in-64 chance of impacting the performance of the subset of the flows > that are mapped via RSS to the interrupt that happens to be assigned to > the CPU where the VM is being torn down. > > Of course, the obvious next question is why not just bind the VMs flows > to the CPUs the VM is running on? We don't have a 1:1 mapping of > network device to VM, or VM to CPU right now, which frustrates this > approach. > > > > Further reducing the stage2_apply_range() batch size has substantial > > > performance improvements for IO that share a CPU performing an unmap > > > operation. By switching to a 2mb chunk, IO performance regressions were > > > no longer observed in this author's tests. E.g. it was possible to > > > obtain the advertised device throughput despite an unmap operation > > > occurring on the CPU where the interrupt was running. There is a > > > tradeoff, however. No changes were observed in per-operation timings > > > when running the kvm_pagetable_test without an interrupt load. However, > > > with a 64gb VM, 1 vcpu, and 4k pages and a IO load, map times increased > > > by about 15% and unmap times increased by about 58%. In essence, this > > > trades slower map/unmap times for improved IO throughput. > > > > There are other users of the range-based operations, like > > write-protection. Live migration is especially sensitive to the latency > > of page table updates as it can affect the VMM's ability to converge > > with the guest. > > To be clear, the reduction in performance was observed when I > concurrently executed both the kvm_pagetable_test and a networking > benchmark where the NIC's interrupts were assigned to the same CPU where > the pagetable test was executing. I didn't see a slowdown just running > the pagetable test. Any chance you could share more details about your HW configuration (what CPU is that?) and the type of traffic? This is the sort of things I'd like to be able to reproduce in order to experiment various strategies. Thanks, M.
Hi Marc, On Sat, Mar 30, 2024 at 10:17:43AM +0000, Marc Zyngier wrote: > On Fri, 29 Mar 2024 19:15:37 +0000, > Krister Johansen <kjlx@templeofstupid.com> wrote: > > On Fri, Mar 29, 2024 at 06:48:38AM -0700, Oliver Upton wrote: > > > On Thu, Mar 28, 2024 at 12:05:08PM -0700, Krister Johansen wrote: > > > > stage2_apply_range() for unmap operations can interfere with the > > > > performance of IO if the device's interrupts share the CPU where the > > > > unmap operation is occurring. commit 5994bc9e05c2 ("KVM: arm64: Limit > > > > stage2_apply_range() batch size to largest block") improved this. Prior > > > > to that commit, workloads that were unfortunate enough to have their IO > > > > interrupts pinned to the same CPU as the unmap operation would observe a > > > > complete stall. With the switch to using the largest block size, it is > > > > possible for IO to make progress, albeit at a reduced speed. > > > > > > Can you describe the workload a bit more? I'm having a hard time > > > understanding how you're unmapping that much memory on the fly in > > > your workload. Is guest memory getting swapped? Are VMs being torn > > > down? > > > > Sorry I wasn't clear here. Yes, it's the VMs getting torn down that's > > causing the problems. The container VMs don't have long lifetimes, but > > some may be up to 256Gb in size, depending on the user. The workloads > > running the VMs aren't especially performance sensitive, but their users > > do notice when network connections time-out. IOW, if the performance is > > bad enough to temporarily prevent new TCP connections from being > > established or requests / responses being recieved in a timely fashion, > > we'll hear about it. Users deploy their services a lot, so there's a > > lot of container vm churn. (Really it's automation redeploying the > > services on behalf of the users in response to new commits to their > > repos...) > > I think this advocates for a teardown-specific code path rather than > just relying on the usual S2 unmapping which is really designed for > eviction. There are two things to consider here: > > - TLB invalidation: this should only take a single VMALLS12E1, rather > than iterating over the PTs > > - Cache maintenance: this could be elided with FWB, or *optionally* > elided if userspace buys in a "I don't need to see the memory of the > guest after teardown" type of behaviour This approach would work for this workload, I think. The hardware supports FWB and AFAIK isn't looking at the guest memory after teardown. This is also desirable because in the future we'd like to support hotplug of VFIO devices. A separate path for unmap the memory used by the device vs unmap all of the guest seems smart. > > > Also, it seems a bit odd to steer interrupts *into* the workload you > > > care about... > > > > Ah, that was only intentionally done for the purposes of measuring the > > impact. That's not done on purpose in production. > > > > Nevertheless, the example we tend to run into is that a box may have 2 > > NICs and each NIC has 32 Tx-Rx queues. This means we've got 64 NIC > > interrupts, each assigned to a different CPU. Our systems have 64 CPUs. > > What happens in practice is that a VM will get torn down, and that has a > > 1-in-64 chance of impacting the performance of the subset of the flows > > that are mapped via RSS to the interrupt that happens to be assigned to > > the CPU where the VM is being torn down. > > > > Of course, the obvious next question is why not just bind the VMs flows > > to the CPUs the VM is running on? We don't have a 1:1 mapping of > > network device to VM, or VM to CPU right now, which frustrates this > > approach. > > > > > > Further reducing the stage2_apply_range() batch size has substantial > > > > performance improvements for IO that share a CPU performing an unmap > > > > operation. By switching to a 2mb chunk, IO performance regressions were > > > > no longer observed in this author's tests. E.g. it was possible to > > > > obtain the advertised device throughput despite an unmap operation > > > > occurring on the CPU where the interrupt was running. There is a > > > > tradeoff, however. No changes were observed in per-operation timings > > > > when running the kvm_pagetable_test without an interrupt load. However, > > > > with a 64gb VM, 1 vcpu, and 4k pages and a IO load, map times increased > > > > by about 15% and unmap times increased by about 58%. In essence, this > > > > trades slower map/unmap times for improved IO throughput. > > > > > > There are other users of the range-based operations, like > > > write-protection. Live migration is especially sensitive to the latency > > > of page table updates as it can affect the VMM's ability to converge > > > with the guest. > > > > To be clear, the reduction in performance was observed when I > > concurrently executed both the kvm_pagetable_test and a networking > > benchmark where the NIC's interrupts were assigned to the same CPU where > > the pagetable test was executing. I didn't see a slowdown just running > > the pagetable test. > > Any chance you could share more details about your HW configuration > (what CPU is that?) and the type of traffic? This is the sort of > things I'd like to be able to reproduce in order to experiment various > strategies. Sure, I only have access to documentation that is publicly available. The hardware where we ran into this inititally was Graviton 3, which is a Neoverse-V1 based core. It does not support FEAT_TLBIRANGE. I've also tested on Graviton 4, which is Neoverse-V2 based. It _does_ support FEAT_TLBIRANGE. The deferred range based invalidation support, was enough to allow us to teardown a large VM based on 4k pages and not incur a visible performance penalty. I haven't had a chance to test to see if and how Will's patches change this, though. The tests themselves were not especially fancy. The networking hardware was a ENA device on an EC2 box with 30Gbps limit (5/10 Gbps per flow, depending on the config). The storage tested was a gp3 EBS device configured to max IOPS/throughput (16,000 IOPS / 1000Mb/s). Networking tests were iperf3 with a 9001 byte packet size. The storage tests were fio's randwrite workload in directio mode using the libaio backend. The "IOPS" test used a 4k blocksize and a queue depth of 128. The "throughput" test used a blocksize of 64k and an iodepth of 32. For the fio tests, it was a 10gb file and 2 workers, mostly because the EBS devices have two hardware queues for data. I ran the kvm_page_table_test with a few different sizes, but settled on 64G with 1 vcpu for most tests. Let me know if there's anything else I can share here. -K
On Tue, Apr 02, 2024 at 10:00:53AM -0700, Krister Johansen wrote: > On Sat, Mar 30, 2024 at 10:17:43AM +0000, Marc Zyngier wrote: > > On Fri, 29 Mar 2024 19:15:37 +0000, > > Krister Johansen <kjlx@templeofstupid.com> wrote: > > > On Fri, Mar 29, 2024 at 06:48:38AM -0700, Oliver Upton wrote: > > > > On Thu, Mar 28, 2024 at 12:05:08PM -0700, Krister Johansen wrote: > > > > > Further reducing the stage2_apply_range() batch size has substantial > > > > > performance improvements for IO that share a CPU performing an unmap > > > > > operation. By switching to a 2mb chunk, IO performance regressions were > > > > > no longer observed in this author's tests. E.g. it was possible to > > > > > obtain the advertised device throughput despite an unmap operation > > > > > occurring on the CPU where the interrupt was running. There is a > > > > > tradeoff, however. No changes were observed in per-operation timings > > > > > when running the kvm_pagetable_test without an interrupt load. However, > > > > > with a 64gb VM, 1 vcpu, and 4k pages and a IO load, map times increased > > > > > by about 15% and unmap times increased by about 58%. In essence, this > > > > > trades slower map/unmap times for improved IO throughput. > > > > > > > > There are other users of the range-based operations, like > > > > write-protection. Live migration is especially sensitive to the latency > > > > of page table updates as it can affect the VMM's ability to converge > > > > with the guest. > > > > > > To be clear, the reduction in performance was observed when I > > > concurrently executed both the kvm_pagetable_test and a networking > > > benchmark where the NIC's interrupts were assigned to the same CPU where > > > the pagetable test was executing. I didn't see a slowdown just running > > > the pagetable test. > > > > Any chance you could share more details about your HW configuration > > (what CPU is that?) and the type of traffic? This is the sort of > > things I'd like to be able to reproduce in order to experiment various > > strategies. > > Sure, I only have access to documentation that is publicly available. > > The hardware where we ran into this inititally was Graviton 3, which is > a Neoverse-V1 based core. It does not support FEAT_TLBIRANGE. I've > also tested on Graviton 4, which is Neoverse-V2 based. It _does_ > support FEAT_TLBIRANGE. The deferred range based invalidation > support, was enough to allow us to teardown a large VM based on 4k pages > and not incur a visible performance penalty. I haven't had a chance to > test to see if and how Will's patches change this, though. Just a quick followup that I did test Will's patches and didn't find that it changed the performance of the workload that I'd been testing. IOW, I wasn't able to discern a network performance difference between the baseline and those changes. Thanks, -K
I measured the time it takes to unmap a VM by changing the kvm_page_table_test to report it. It's and on Graviton3 it's about 300ms per 1GB of flushing with 4KB pages. Unmapping 128GB takes around 39.5s and with a single call to __kvm_tlb_flush_vmid() instead of the 32M calls to __kvm_tlb_flush_vmid_ipa() reduces this to around 5.9s (~7x). This means each iteration of the stage2_apply_range() is reduced to 46ms. So we're certainly calling cond_resched() a whole lot more. > Just a quick followup that I did test Will's patches and didn't find > that it changed the performance of the workload that I'd been testing. > IOW, I wasn't able to discern a network performance difference between > the baseline and those changes. That is a bit unexpected that the performance wasn't worse with the patch Will sent because it should have disabled the range invalidates since they these invalidates will be getting rid of blocks? Which Graviton were you testing this on? Ali
On Thu, Apr 04, 2024 at 09:27:42PM +0000, Ali Saidi wrote: > > Just a quick followup that I did test Will's patches and didn't find > > that it changed the performance of the workload that I'd been testing. > > IOW, I wasn't able to discern a network performance difference between > > the baseline and those changes. > > That is a bit unexpected that the performance wasn't worse with the patch Will > sent because it should have disabled the range invalidates since they these > invalidates will be getting rid of blocks? Which Graviton were you testing > this on? Sorry I didn't mention it earlier. This was on a Graviton 4 with FEAT_TLBIRANGE. Due to the placement of the test machine and the client the max single flow rate was 5Gbps, and with both the baseline and Will's patches I wasn't able to discern any slowdown there, at least in terms of impact to the adjacent networking traffic. I saw an approx 1% slowdown with multiple flows at 10Gbps, but didn't have a baseline for that test case so was hesitant to offer it as conclusive. I should be clear that I _wasn't_ measuring the the teardown times in this test -- just how the teardown itself impacted the networking performance. -K
diff --git a/arch/arm64/include/asm/kvm_pgtable.h b/arch/arm64/include/asm/kvm_pgtable.h index 19278dfe7978..b0c4651a4d9a 100644 --- a/arch/arm64/include/asm/kvm_pgtable.h +++ b/arch/arm64/include/asm/kvm_pgtable.h @@ -19,11 +19,15 @@ * - 4K (level 1): 1GB * - 16K (level 2): 32MB * - 64K (level 2): 512MB + * + * The max block level is the _smallest_ supported block size for KVM. */ #ifdef CONFIG_ARM64_4K_PAGES #define KVM_PGTABLE_MIN_BLOCK_LEVEL 1 +#define KVM_PGTABLE_MAX_BLOCK_LEVEL 2 #else #define KVM_PGTABLE_MIN_BLOCK_LEVEL 2 +#define KVM_PGTABLE_MAX_BLOCK_LEVEL KVM_PGTABLE_MIN_BLOCK_LEVEL #endif #define kvm_lpa2_is_enabled() system_supports_lpa2() diff --git a/arch/arm64/kvm/mmu.c b/arch/arm64/kvm/mmu.c index dc04bc767865..1e927b306aee 100644 --- a/arch/arm64/kvm/mmu.c +++ b/arch/arm64/kvm/mmu.c @@ -41,7 +41,7 @@ static phys_addr_t __stage2_range_addr_end(phys_addr_t addr, phys_addr_t end, static phys_addr_t stage2_range_addr_end(phys_addr_t addr, phys_addr_t end) { - phys_addr_t size = kvm_granule_size(KVM_PGTABLE_MIN_BLOCK_LEVEL); + phys_addr_t size = kvm_granule_size(KVM_PGTABLE_MAX_BLOCK_LEVEL); return __stage2_range_addr_end(addr, end, size); }
stage2_apply_range() for unmap operations can interfere with the performance of IO if the device's interrupts share the CPU where the unmap operation is occurring. commit 5994bc9e05c2 ("KVM: arm64: Limit stage2_apply_range() batch size to largest block") improved this. Prior to that commit, workloads that were unfortunate enough to have their IO interrupts pinned to the same CPU as the unmap operation would observe a complete stall. With the switch to using the largest block size, it is possible for IO to make progress, albeit at a reduced speed. This author tested network and storage where the interrupts were pinned to the same CPU where an unmap was occurring and found that throughput was reduced about 4.75-5.8x for networking, and 65.5x-500x for storage. The use-case where this has been especially painful is with hardware virtualized containers. Many containers have a short lifetime and may be run on systems where the host is intentionally oversubscribed. This limits the options for pinning and prefaulting. Although NIC interrupts allow their CPU affinity to be altered, some NVMe devices do not permit it. Some cloud-block storage devices have only a few queues, which means unlucky placement can have high performance impact. Further reducing the stage2_apply_range() batch size has substantial performance improvements for IO that share a CPU performing an unmap operation. By switching to a 2mb chunk, IO performance regressions were no longer observed in this author's tests. E.g. it was possible to obtain the advertised device throughput despite an unmap operation occurring on the CPU where the interrupt was running. There is a tradeoff, however. No changes were observed in per-operation timings when running the kvm_pagetable_test without an interrupt load. However, with a 64gb VM, 1 vcpu, and 4k pages and a IO load, map times increased by about 15% and unmap times increased by about 58%. In essence, this trades slower map/unmap times for improved IO throughput. This introduces KVM_PGTABLE_MAX_BLOCK_LEVEL, and then uses it to limit the size of stage2_apply_range() chunks to the smallest size that's addressable via a block mapping -- 2mb on a 4k granule size. Cc: <stable@vger.kernel.org> # 5.15.x: 3b5c082bbfa2: KVM: arm64: Work out supported block level at compile time Cc: <stable@vger.kernel.org> # 5.15.x: 5994bc9e05c2: KVM: arm64: Limit stage2_apply_range() batch size to largest block Cc: <stable@vger.kernel.org> # 5.15.x Suggested-by: Ali Saidi <alisaidi@amazon.com> Signed-off-by: Krister Johansen <kjlx@templeofstupid.com> --- arch/arm64/include/asm/kvm_pgtable.h | 4 ++++ arch/arm64/kvm/mmu.c | 2 +- 2 files changed, 5 insertions(+), 1 deletion(-)