ACRN Real-Time (RT) Performance Analysis¶
The document describes the methods to collect trace/data for ACRN real-time VM (RTVM) real-time performance analysis. Two parts are included:
Method to trace
vmexit
occurrences for analysis.Method to collect Performance Monitoring Counters information for tuning based on Performance Monitoring Unit, or PMU.
vmexit Analysis for ACRN RT Performance¶
vmexit
are triggered in response to certain instructions and events and are
a key source of performance degradation in virtual machines. During the runtime
of a hard RTVM of ACRN, the following impacts real-time deterministic latency:
CPUID
TSC_Adjust read/write
TSC write
APICID/LDR read
ICR write
Generally, we don’t want to see any vmexit
occur during the critical section of the RT task.
The methodology of vmexit
analysis is very simple. First, we clearly
identify the critical section of the RT task. The critical section is
the duration of time where we do not want to see any vmexit
occur.
Different RT tasks use different critical sections. This document uses
the cyclictest benchmark as an example of how to do vmexit
analysis.
The Critical Sections¶
Here is example pseudocode of a cyclictest implementation.
while (!shutdown) {
...
clock_nanosleep(&next)
clock_gettime(&now)
latency = calcdiff(now, next)
...
next += interval
}
Time point now
is the actual point at which the cyclictest app is woken up
and scheduled. Time point next
is the expected point at which we want
the cyclictest to be awakened and scheduled. Here we can get the latency by
now - next
. We don’t want to see a vmexit
in between next
and now
.
So, we define the starting point of the critical section as next
and
the ending point as now
.
Log and Trace Data Collection¶
Add time stamps (in TSC) at
next
andnow
.Capture the log with the above time stamps in the RTVM.
Capture the
acrntrace
log in the Service VM at the same time.
Offline Analysis¶
Convert the raw trace data to human readable format.
Merge the logs in the RTVM and the ACRN hypervisor trace based on time stamps (in TSC).
Check to see if any
vmexit
occurred within the critical sections. The pattern is as follows:
Collecting Performance Monitoring Counters Data¶
Performance Monitoring Unit (PMU) Support for the RTVM¶
By default, the ACRN hypervisor exposes the PMU-related CPUID and MSRs to the RTVM. Note that Precise Event Based Sampling (PEBS) is not yet enabled in the VM.
Perf/PMU Tools in Performance Analysis¶
Since users no longer need to expose PMU-related CPUID/MSRs to the VM, performance analysis tools
such as perf
and PMU
can be used inside the VM to locate
the bottleneck of the application.
Perf
is a profiler tool for Linux 2.6+ based systems that abstracts away
CPU hardware differences in Linux performance measurements and presents a
simple command-line interface. Perf is based on the perf_events
interface
exported by recent versions of the Linux kernel.
PMU tools
is a collection of tools for profile collection and
performance analysis on Intel CPUs on top of Linux Perf. Refer to the
following links for perf usage:
Refer to https://github.com/andikleen/pmu-tools for PMU usage.
Top-Down Microarchitecture Analysis Method (TMAM)¶
The top-down microarchitecture analysis method (TMAM), based on top-down characterization methodology, aims to provide an insight into whether you have made wise choices with your algorithms and data structures. See the Intel® 64 and IA-32 Architectures Optimization Reference Manual, Appendix B.1 for more details on TMAM. Refer to this technical paper that adopts TMAM for systematic performance benchmarking and analysis of compute-native Network Function data planes that are executed on commercial-off-the-shelf (COTS) servers using available open-source measurement tools.
Example: Using Perf to analyze TMAM level 1 on CPU core 1:
perf stat --topdown -C 1 taskset -c 1 dd if=/dev/zero of=/dev/null count=10 10+0 records in 10+0 records out 5120 bytes (5.1 kB, 5.0 KiB) copied, 0.00336348 s, 1.5 MB/s Performance counter stats for 'CPU(s) 1': retiring bad speculation frontend bound backend bound S0-C1 1 10.6% 1.5% 3.9% 84.0% 0.006737123 seconds time elapsed