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I really needed this, like, factually, yesterday, when verifying dependency breaking idioms for AMD Zen 3 scheduler model. Consider the following example: ``` $ ./bin/llvm-exegesis --mode=inverse_throughput --snippets-file=/tmp/snippet.s --num-repetitions=1000000 --repetition-mode=duplicate Check generated assembly with: /usr/bin/objdump -d /tmp/snippet-4a7e50.o --- mode: inverse_throughput key: instructions: - 'VPXORYrr YMM0 YMM0 YMM0' config: '' register_initial_values: [] cpu_name: znver3 llvm_triple: x86_64-unknown-linux-gnu num_repetitions: 1000000 measurements: - { key: inverse_throughput, value: 0.31025, per_snippet_value: 0.31025 } error: '' info: '' assembled_snippet: C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C5FDEFC0C3 ... ``` What does it tell us? So wait, it can only execute ~3 x86 AVX YMM PXOR zero-idioms per cycle? That doesn't seem right. That's even less than there are pipes supporting this type of op. Now, second example: ``` $ ./bin/llvm-exegesis --mode=inverse_throughput --snippets-file=/tmp/snippet.s --num-repetitions=1000000 --repetition-mode=loop Check generated assembly with: /usr/bin/objdump -d /tmp/snippet-2418b5.o --- mode: inverse_throughput key: instructions: - 'VPXORYrr YMM0 YMM0 YMM0' config: '' register_initial_values: [] cpu_name: znver3 llvm_triple: x86_64-unknown-linux-gnu num_repetitions: 1000000 measurements: - { key: inverse_throughput, value: 1.00011, per_snippet_value: 1.00011 } error: '' info: '' assembled_snippet: 49B80800000000000000C5FDEFC0C5FDEFC04983C0FF75F2C3 ... ``` Now that's just worse. Due to the looping, the throughput completely plummeted, and now we can only do a single instruction/cycle!? That's not great. And final example: ``` $ ./bin/llvm-exegesis --mode=inverse_throughput --snippets-file=/tmp/snippet.s --num-repetitions=1000000 --repetition-mode=loop --loop-body-size=1000 Check generated assembly with: /usr/bin/objdump -d /tmp/snippet-c402e2.o --- mode: inverse_throughput key: instructions: - 'VPXORYrr YMM0 YMM0 YMM0' config: '' register_initial_values: [] cpu_name: znver3 llvm_triple: x86_64-unknown-linux-gnu num_repetitions: 1000000 measurements: - { key: inverse_throughput, value: 0.167087, per_snippet_value: 0.167087 } error: '' info: '' assembled_snippet: 49B80800000000000000C5FDEFC0C5FDEFC04983C0FF75F2C3 ... ``` So if we merge the previous two approaches, do duplicate this single-instruction snippet 1000x (loop-body-size/instruction count in snippet), and run a loop with 1000 iterations over that duplicated/unrolled snippet, the measured throughput goes through the roof, up to 5.9 instructions/cycle, which finally tells us that this idiom is zero-cycle! Reviewed By: courbet Differential Revision: https://reviews.llvm.org/D102522
312 lines
12 KiB
ReStructuredText
312 lines
12 KiB
ReStructuredText
llvm-exegesis - LLVM Machine Instruction Benchmark
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==================================================
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.. program:: llvm-exegesis
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SYNOPSIS
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--------
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:program:`llvm-exegesis` [*options*]
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DESCRIPTION
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-----------
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:program:`llvm-exegesis` is a benchmarking tool that uses information available
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in LLVM to measure host machine instruction characteristics like latency,
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throughput, or port decomposition.
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Given an LLVM opcode name and a benchmarking mode, :program:`llvm-exegesis`
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generates a code snippet that makes execution as serial (resp. as parallel) as
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possible so that we can measure the latency (resp. inverse throughput/uop decomposition)
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of the instruction.
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The code snippet is jitted and executed on the host subtarget. The time taken
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(resp. resource usage) is measured using hardware performance counters. The
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result is printed out as YAML to the standard output.
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The main goal of this tool is to automatically (in)validate the LLVM's TableDef
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scheduling models. To that end, we also provide analysis of the results.
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:program:`llvm-exegesis` can also benchmark arbitrary user-provided code
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snippets.
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EXAMPLE 1: benchmarking instructions
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------------------------------------
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Assume you have an X86-64 machine. To measure the latency of a single
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instruction, run:
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.. code-block:: bash
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$ llvm-exegesis -mode=latency -opcode-name=ADD64rr
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Measuring the uop decomposition or inverse throughput of an instruction works similarly:
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.. code-block:: bash
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$ llvm-exegesis -mode=uops -opcode-name=ADD64rr
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$ llvm-exegesis -mode=inverse_throughput -opcode-name=ADD64rr
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The output is a YAML document (the default is to write to stdout, but you can
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redirect the output to a file using `-benchmarks-file`):
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.. code-block:: none
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---
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key:
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opcode_name: ADD64rr
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mode: latency
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config: ''
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cpu_name: haswell
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llvm_triple: x86_64-unknown-linux-gnu
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num_repetitions: 10000
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measurements:
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- { key: latency, value: 1.0058, debug_string: '' }
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error: ''
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info: 'explicit self cycles, selecting one aliasing configuration.
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Snippet:
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ADD64rr R8, R8, R10
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'
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...
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To measure the latency of all instructions for the host architecture, run:
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.. code-block:: bash
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$ llvm-exegesis -mode=latency -opcode-index=-1
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EXAMPLE 2: benchmarking a custom code snippet
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---------------------------------------------
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To measure the latency/uops of a custom piece of code, you can specify the
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`snippets-file` option (`-` reads from standard input).
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.. code-block:: bash
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$ echo "vzeroupper" | llvm-exegesis -mode=uops -snippets-file=-
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Real-life code snippets typically depend on registers or memory.
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:program:`llvm-exegesis` checks the liveliness of registers (i.e. any register
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use has a corresponding def or is a "live in"). If your code depends on the
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value of some registers, you have two options:
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- Mark the register as requiring a definition. :program:`llvm-exegesis` will
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automatically assign a value to the register. This can be done using the
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directive `LLVM-EXEGESIS-DEFREG <reg name> <hex_value>`, where `<hex_value>`
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is a bit pattern used to fill `<reg_name>`. If `<hex_value>` is smaller than
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the register width, it will be sign-extended.
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- Mark the register as a "live in". :program:`llvm-exegesis` will benchmark
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using whatever value was in this registers on entry. This can be done using
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the directive `LLVM-EXEGESIS-LIVEIN <reg name>`.
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For example, the following code snippet depends on the values of XMM1 (which
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will be set by the tool) and the memory buffer passed in RDI (live in).
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.. code-block:: none
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# LLVM-EXEGESIS-LIVEIN RDI
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# LLVM-EXEGESIS-DEFREG XMM1 42
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vmulps (%rdi), %xmm1, %xmm2
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vhaddps %xmm2, %xmm2, %xmm3
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addq $0x10, %rdi
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EXAMPLE 3: analysis
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-------------------
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Assuming you have a set of benchmarked instructions (either latency or uops) as
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YAML in file `/tmp/benchmarks.yaml`, you can analyze the results using the
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following command:
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.. code-block:: bash
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$ llvm-exegesis -mode=analysis \
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-benchmarks-file=/tmp/benchmarks.yaml \
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-analysis-clusters-output-file=/tmp/clusters.csv \
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-analysis-inconsistencies-output-file=/tmp/inconsistencies.html
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This will group the instructions into clusters with the same performance
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characteristics. The clusters will be written out to `/tmp/clusters.csv` in the
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following format:
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.. code-block:: none
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cluster_id,opcode_name,config,sched_class
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...
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2,ADD32ri8_DB,,WriteALU,1.00
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2,ADD32ri_DB,,WriteALU,1.01
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2,ADD32rr,,WriteALU,1.01
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2,ADD32rr_DB,,WriteALU,1.00
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2,ADD32rr_REV,,WriteALU,1.00
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2,ADD64i32,,WriteALU,1.01
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2,ADD64ri32,,WriteALU,1.01
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2,MOVSX64rr32,,BSWAP32r_BSWAP64r_MOVSX64rr32,1.00
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2,VPADDQYrr,,VPADDBYrr_VPADDDYrr_VPADDQYrr_VPADDWYrr_VPSUBBYrr_VPSUBDYrr_VPSUBQYrr_VPSUBWYrr,1.02
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2,VPSUBQYrr,,VPADDBYrr_VPADDDYrr_VPADDQYrr_VPADDWYrr_VPSUBBYrr_VPSUBDYrr_VPSUBQYrr_VPSUBWYrr,1.01
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2,ADD64ri8,,WriteALU,1.00
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2,SETBr,,WriteSETCC,1.01
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...
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:program:`llvm-exegesis` will also analyze the clusters to point out
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inconsistencies in the scheduling information. The output is an html file. For
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example, `/tmp/inconsistencies.html` will contain messages like the following :
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.. image:: llvm-exegesis-analysis.png
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:align: center
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Note that the scheduling class names will be resolved only when
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:program:`llvm-exegesis` is compiled in debug mode, else only the class id will
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be shown. This does not invalidate any of the analysis results though.
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OPTIONS
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-------
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.. option:: -help
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Print a summary of command line options.
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.. option:: -opcode-index=<LLVM opcode index>
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Specify the opcode to measure, by index. Specifying `-1` will result
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in measuring every existing opcode. See example 1 for details.
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Either `opcode-index`, `opcode-name` or `snippets-file` must be set.
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.. option:: -opcode-name=<opcode name 1>,<opcode name 2>,...
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Specify the opcode to measure, by name. Several opcodes can be specified as
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a comma-separated list. See example 1 for details.
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Either `opcode-index`, `opcode-name` or `snippets-file` must be set.
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.. option:: -snippets-file=<filename>
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Specify the custom code snippet to measure. See example 2 for details.
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Either `opcode-index`, `opcode-name` or `snippets-file` must be set.
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.. option:: -mode=[latency|uops|inverse_throughput|analysis]
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Specify the run mode. Note that some modes have additional requirements and options.
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`latency` mode can be make use of either RDTSC or LBR.
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`latency[LBR]` is only available on X86 (at least `Skylake`).
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To run in `latency` mode, a positive value must be specified
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for `x86-lbr-sample-period` and `--repetition-mode=loop`.
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In `analysis` mode, you also need to specify at least one of the
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`-analysis-clusters-output-file=` and `-analysis-inconsistencies-output-file=`.
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.. option:: -x86-lbr-sample-period=<nBranches/sample>
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Specify the LBR sampling period - how many branches before we take a sample.
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When a positive value is specified for this option and when the mode is `latency`,
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we will use LBRs for measuring.
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On choosing the "right" sampling period, a small value is preferred, but throttling
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could occur if the sampling is too frequent. A prime number should be used to
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avoid consistently skipping certain blocks.
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.. option:: -repetition-mode=[duplicate|loop|min]
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Specify the repetition mode. `duplicate` will create a large, straight line
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basic block with `num-repetitions` instructions (repeating the snippet
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`num-repetitions`/`snippet size` times). `loop` will, optionally, duplicate the
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snippet until the loop body contains at least `loop-body-size` instructions,
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and then wrap the result in a loop which will execute `num-repetitions`
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instructions (thus, again, repeating the snippet
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`num-repetitions`/`snippet size` times). The `loop` mode, especially with loop
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unrolling tends to better hide the effects of the CPU frontend on architectures
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that cache decoded instructions, but consumes a register for counting
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iterations. If performing an analysis over many opcodes, it may be best to
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instead use the `min` mode, which will run each other mode,
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and produce the minimal measured result.
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.. option:: -num-repetitions=<Number of repetitions>
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Specify the target number of executed instructions. Note that the actual
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repetition count of the snippet will be `num-repetitions`/`snippet size`.
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Higher values lead to more accurate measurements but lengthen the benchmark.
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.. option:: -loop-body-size=<Preferred loop body size>
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Only effective for `-repetition-mode=[loop|min]`.
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Instead of looping over the snippet directly, first duplicate it so that the
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loop body contains at least this many instructions. This potentially results
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in loop body being cached in the CPU Op Cache / Loop Cache, which allows to
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which may have higher throughput than the CPU decoders.
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.. option:: -max-configs-per-opcode=<value>
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Specify the maximum configurations that can be generated for each opcode.
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By default this is `1`, meaning that we assume that a single measurement is
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enough to characterize an opcode. This might not be true of all instructions:
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for example, the performance characteristics of the LEA instruction on X86
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depends on the value of assigned registers and immediates. Setting a value of
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`-max-configs-per-opcode` larger than `1` allows `llvm-exegesis` to explore
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more configurations to discover if some register or immediate assignments
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lead to different performance characteristics.
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.. option:: -benchmarks-file=</path/to/file>
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File to read (`analysis` mode) or write (`latency`/`uops`/`inverse_throughput`
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modes) benchmark results. "-" uses stdin/stdout.
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.. option:: -analysis-clusters-output-file=</path/to/file>
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If provided, write the analysis clusters as CSV to this file. "-" prints to
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stdout. By default, this analysis is not run.
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.. option:: -analysis-inconsistencies-output-file=</path/to/file>
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If non-empty, write inconsistencies found during analysis to this file. `-`
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prints to stdout. By default, this analysis is not run.
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.. option:: -analysis-clustering=[dbscan,naive]
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Specify the clustering algorithm to use. By default DBSCAN will be used.
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Naive clustering algorithm is better for doing further work on the
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`-analysis-inconsistencies-output-file=` output, it will create one cluster
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per opcode, and check that the cluster is stable (all points are neighbours).
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.. option:: -analysis-numpoints=<dbscan numPoints parameter>
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Specify the numPoints parameters to be used for DBSCAN clustering
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(`analysis` mode, DBSCAN only).
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.. option:: -analysis-clustering-epsilon=<dbscan epsilon parameter>
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Specify the epsilon parameter used for clustering of benchmark points
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(`analysis` mode).
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.. option:: -analysis-inconsistency-epsilon=<epsilon>
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Specify the epsilon parameter used for detection of when the cluster
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is different from the LLVM schedule profile values (`analysis` mode).
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.. option:: -analysis-display-unstable-clusters
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If there is more than one benchmark for an opcode, said benchmarks may end up
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not being clustered into the same cluster if the measured performance
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characteristics are different. by default all such opcodes are filtered out.
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This flag will instead show only such unstable opcodes.
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.. option:: -ignore-invalid-sched-class=false
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If set, ignore instructions that do not have a sched class (class idx = 0).
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.. option:: -mcpu=<cpu name>
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If set, measure the cpu characteristics using the counters for this CPU. This
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is useful when creating new sched models (the host CPU is unknown to LLVM).
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.. option:: --dump-object-to-disk=true
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By default, llvm-exegesis will dump the generated code to a temporary file to
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enable code inspection. You may disable it to speed up the execution and save
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disk space.
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EXIT STATUS
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-----------
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:program:`llvm-exegesis` returns 0 on success. Otherwise, an error message is
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printed to standard error, and the tool returns a non 0 value.
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