• Perfmon Metrics
• Top-down Microarchitecture Analysis (TMA)
• Perfmon Events
• How to Contribute
• Support

Perfmon Metrics is a set of metric files and scripts used to perform performance analysis of systems. This repo has three parts

1. List of generically formatted json files for metric equations per platform

2. Scripts for processing the generic format of the metric equations into common tool formats

3. Documentation on how to analyze the metric and the output

• MetricName: The string name of the metric being defined.

• Level: Integer value representing the relationship of this metric in a hierarchy of metrics. This field can be used along with "ParentCategory" to define a tree structure of metrics. Root level metrics have a level of 1.

• BriefDescription: The description of what the metric is measuring. Long descriptions will be in the documents section of this GitHub.

• UnitOfMeasure: The unit of measure for a metric, can be time, frequency, number of samples, percent.

• Events: List of events and their alias which is used in the formula.

  • Name: The name of the event from the JSON event list in the event list folder. May change per platform.

  • Alias: The alias used for the event in the formula.

• Constants: List of constants required for the given metric with the same fields as those defined for the event list: Name and Alias.

• Formula: String providing the arithmetic to be performed to form the metric value based on the provided aliases.

• Category: Useful tagging for the metric. Intended to be used for parsing when creating a subset of metrics list. Some categories will be general, IO, TMA, microservices

• Threshold: When the threshold evaluates as true then it indicates that this metric is meaningful for the current analysis. <sign> X requires that the value of the node should hold true the relationship with X. P requires that the nodes parent needs to pass the threshold for this to be true. ; separator, & and, | or $issueXX is a unique tag that associates together multiple nodes from different categories of the tree. For example, Bad_Speculation is tightly coupled with Branch_Resteers (from the Frontend_Bound Category). ~overlap indicates a weight of a specific node overlaps with its siblings. I.e. their costs are not mutually exclusive. For example, value of Branch_Resteers may overlap with ICache_Misses. Example: > 0.2 & P means the current node's values is above 20% and the Parent node is highlighted.

• ResolutionLevels: List of resolution levels that tools can choose to compute for the given metric. For example, if the list contains THREAD, then the metric can be computed at a per thread level. The metric is not valid when data is aggregated at a level not present in the resolution level list. If the list contains THREAD, CORE, SOCKET, SYSTEM then this indicates that a tool can choose to compute this metric at the thread level, or aggregate counts across core or socket or system level to report a broader metric resolution.

• MetricGroup: Grouping for perf, further explanation added on perf script release.

• CHAS_PER_SOCKET: The number of CHA units per socket. The CHA is the Caching and Home Agent and the number of CHAs per socket is SKU dependent but often matches the number of cores per socket.
• CORES_PER_SOCKET: The number of cores per socket.
• DURATIONTIMEINSECONDS: The time interval in seconds that performance monitoring counter data was collected.
• SOCKET_COUNT: The number of sockets on the system.
• TSC: Duration time in cycles
• SYSTEM_TSC_FREQ: The TSC frequency metadata specific to the system being profiled in MHz.

1. Python3+

2. perf v6.0 (recommend the newest version of perf available)

3. linux kernel version v5.11

The perf script in /scripts will take the metrics.json file and convert that generic format to a perf specific metrics file. See the pre-built metrics_icx_perf.json file in the scripts folder as a perf compatible version of the metrics that the script will generate.

1. How to build with perf

   1.1 Create working directory

   mkdir perfmon-metrics

   cd perfmon-metrics

   1.2 Clone the metric repository into the working directory

   git clone https://github.com/intel/perfmon.git

   1.3 Clone a copy of linux source code

   git clone https://github.com/torvalds/linux.git

   1.4 Copy the ICX metric file in the linux perf codebase

   cp ICX/metrics/perf/icx_metrics_perf.json <linux kernel source root dir>/tools/perf/pmu-events/arch/x86/icelakex/

   1.5 Build linux perf (Note: You will need to install dependencies)

   cd <linux kernel source root directory>/tools/perf

   make

2. Local copy of perf will now be built with the new metrics for Icelake systems

   ./perf stat -M <metric_name> -a -- <app>

3. Examples

   ./perf stat -M cpu_utilization_percent -a -- ./mlc

1. Metrics: Memory Bound, Ports Utilization, Core Bound and Fetch Bandwidth may produce incorrect results on HSX and BDX under multi-threaded conditions.

1. A Top-Down Method for Performance Analysis and Counters Architecture. Ahmad Yasin. In IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2014.

In this repository there are three, related, metrics file types.

This package contains performance monitoring event lists for Intel processors, as well as a mapping file to help match event lists to processor Family/Model/Stepping codes.

Event lists are available in JSON (.json) format.

Event lists are created per microarchitecture, and each has a version. Versions are listed in the event list header for each file and mapfile.csv. For some microarchitectures, up to three different event lists will be available. These event lists correspond to the types of events that can be collected:

The event list filename indicates which type of list it contains, and follows this format:

<microarchitecture-codename>_<core/uncore/uncore_experimental/matrix>

New version releases will be announced via GitHub. Please subscribe to release notifications.

Different microarchitectures provide different performance monitoring capabilities, so field names and categories of events may vary.

The following files are distributed under the terms of the 3-clause BSD license:

• Mapfile.csv
• All .json files

Other files in this package are ALL RIGHTS RESERVED.

Below is a list of the fields/headers in the event files and a description of how SW tools should interpret these values. A particular event list from this package may not contain all the fields described below. For more detailed information of the Performance monitoring unit please refer to chapters 18 and 19 of Intel (R) 64 and IA-32 Architectures Software Developer's Manual Volume 3B: System Programming Guide, Part 2.

https://www.intel.com/content/www/us/en/developer/articles/technical/intel-sdm.html

This field maps to the Event Select field in the IA32_PERFEVTSELx[7:0] MSRs. The set of values for this field is defined architecturally. Each value corresponds to an event logic unit and should be used with a unit mask value to obtain an architectural performance event.

This field maps to the Unit Mask filed in the IA32_PERFEVTSELx[15:8] MSRs. It further qualifies the event logic unit selected in the event select field to detect a specific micro-architectural condition.

It is a string of characters to identify the programming of an event.

This field contains a description of what is being counted by a particular event.

In some cases, this field will contain a more detailed description of what is counted by an event.

This field lists the fixed (PERF_FIXED_CTRX) or programmable (IA32_PMCX) counters that can be used to count the event.

This field lists the counters where this event can be sampled when Intel (R) Hyper-Threading Technology (Intel (R) HT Technology) is disabled. When Intel (R) HT Technology is disabled, some processor cores gain access to the programmable counters of the second thread, making a total of eight programmable counters available. The additional counters will be numbered 4,5,6,7. Fixed counter behavior remains unaffected.

This field is only relevant to PEBS events. It lists the counters where the event can be sampled when it is programmed as a PEBS event.

Sample After Value (SAV) is the value that can be pre-loaded into the counter registers to set the point at which they will overflow. To make the counter overflow after N occurrences of the event, it should be loaded with (0xFF..FF - N) or -(N-1). On overflow a hardware interrupt is generated through the Local APIC and additional architectural state can be collected in the interrupt handler. This is useful in event-based sampling. This field gives a recommended default overflow value, which may be adjusted based on workload or tool preference.

Additional MSRs may be required for programming certain events. This field gives the address of such MSRS. Examples include:

• 0x3F6: MSR_PEBS_LD_LAT - used to configure the Load Latency Performance Monitoring Facility
• 0x1A6/0x1A7: MSR_OFFCORE_RSP_X - used to configure the offcore response events

When an MSRIndex is used (indicated by MSRIndex), this field will contain the value that needs to be loaded into the register whose address is given in MSRIndex. For example, in the case of the load latency events, MSRValue defines the latency threshold value to write into the MSR defined in MSRIndex (0x3F6).

Applies to processors that support both precise and non-precise events in Processor Event Based Sampling, such as Goldmont.

0. The event cannot be programmed to collect a PEBS record.
1. The event may be programmed to collect a PEBS record, but caution is advised. For instance, PEBS collection of this event may consume limited PEBS resources whereas interrupt-based sampling may be sufficient for the usage model.
2. The event may be programmed to collect a PEBS record, and due to the nature of the event, PEBS collection may be preferred. For instance, PEBS collection of Goldmont's HW_INTERUPTS.RECIEVED event is recommended because the hardware interrupt being counted may lead to the masking of interrupts which would interfere with interrupt-based sampling.
3. The event must be programmed to collect a PEBS record.

This field is set for an event which can only be sampled or counted by itself, meaning that when this event is being collected, the remaining programmable counters are not available to count any other events.

This field maps to the Counter Mask (CMASK) field in IA32_PERFEVTSELx[31:24] MSR.

This field corresponds to the Invert Counter Mask (INV) field in IA32_PERFEVTSELx[23] MSR.

This field corresponds to the Any Thread (ANY) bit of IA32_PERFEVTSELx[21] MSR.

This field corresponds to the Edge Detect (E) bit of IA32_PERFEVTSELx[18] MSR.

A '0' in this field means that the event cannot collect a PEBS record with a Precise IP. A '1' in this field means that the event is a precise event and can be programmed in one of two ways - as a regular event or as a PEBS event. And a '2' in this field means that the event can only be programmed as a PEBS event.

⚠️ Starting with ICL, ICX, and subsequent platforms, downstream tools will need to reference CollectPEBSRecord and Precise attributes instead of PEBS. Please refer to intel#114 for additional information.

PDist (Precise distribution) eliminates any skid or shadowing effects from PEBS. With PDist, the PEBS record will be generated precisely upon completion of the instruction or operation that causes the counter to overflow (there is no "wait for next occurrence" by default). ¹

The core event attribute Precise indicates if an event can collect a precise eventing instruction pointer in the PEBS record.

For precise events, upon triggering a PEBS assist, there will be a finite delay between the time the counter overflows and when the microcode starts to carry out its data collection obligations. The Reduced Skid mechanism mitigates the "skid" problem by providing an early indication of when the counter is about to overflow, allowing the machine to more precisely trap on the instruction that actually caused the counter overflow thus greatly reducing skid. ²

A '1' in this field means the event uses the Precise Store feature and Bit 3 and bit 63 in IA32_PEBS_ENABLE MSR must be set to enable IA32_PMC3 as a PEBS counter and enable the precise store facility respectively. Processors based on SandyBridge and IvyBridge micro-architecture offer a precise store capability that provides a means to profile store memory references in the system.

A '1' in this field means that when the event is configured as a PEBS event, the Data Linear Address facility is supported. The Data Linear Address facility is a new feature added to Haswell as a replacement or extension of the precise store facility in SNB.

A '1' in this field means that when the event is configured as a PEBS event, the DCU hit field of the PEBS record is set to 1 when the store hits in the L1 cache and 0 when it misses.

This field lists the known bugs that apply to the events. For the latest errata information refer to the following specification updates.

This field is specific to the json format. There is only 1 file for core and offcore events in this format. This field is set to 1 for offcore events and 0 for core events.

Please use SNR core event files. The EHL events folder is populated with a copy of SNR core.json for convenience.

• Event documentation https://perfmon-events.intel.com/
• Intel© Platform Analysis Technology https://www.intel.com/content/www/us/en/developer/topic-technology/platform-analysis-technology/overview.html
• Monitoring Integrated Memory Controller Requests in the 2nd, 3rd, 4th, 5th, 6th generation Intel© Core™ processors https://www.intel.com/content/www/us/en/developer/articles/technical/monitoring-integrated-memory-controller-requests-in-the-2nd-3rd-and-4th-generation-intel.html

1. Report issues with metrics by opening a GitHub Issue.
2. Contribute new metrics along with a metrics test through pull requests. Moderators will test and validate the new metric on specified platforms before merging.
3. Add new scripts for conversions to other performance collection tools.

Open a GitHub Issue and describe any requested changes and their associated platforms. Event lists are generated from a database and not directly edited. Pull requests editing event files will be closed and recreated as a GitHub Issue.

1. Please open a GitHub Issue. Additional performance monitoring users likely have the same question. This option is the recommended support method.
2. If opening a GitHub Issue is not a viable option, please email [email protected]. Include platform configuration, event details, and relevant workload information if possible.

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