nanoBench

nanoBench is a Linux-based tool for running small microbenchmarks on recent Intel and AMD x86 CPUs. The microbenchmarks are evaluated using hardware performance counters. The reading of the performance counters is implemented in a way that incurs only minimal overhead.

There are two variants of the tool: A user-space implementation and a kernel module. The kernel module makes it possible to benchmark privileged instructions, to use uncore performance counters, and it can allow for more accurate measurement results as it disables interrupts and preemptions during measurements. The disadvantage of the kernel module compared to the user-space variant is that it is quite risky to allow arbitrary code to be executed in kernel space. Therefore, the kernel module should not be used on a production system.

nanoBench is used for running the microbenchmarks for obtaining the latency, throughput, and port usage data that is available on uops.info.

More information about nanoBench can be found in the paper nanoBench: A Low-Overhead Tool for Running Microbenchmarks on x86 Systems.

Installation

User-space Version

sudo apt install msr-tools
git clone https://github.com/andreas-abel/nanoBench.git
cd nanoBench
make user

nanoBench might not work if Secure Boot is enabled. Click here for instructions on how to disable Secure Boot.

Kernel Module

Note: The following is not necessary if you would just like to use the user-space version.

sudo apt install python3 python3-pip
pip3 install plotly
git clone https://github.com/andreas-abel/nanoBench.git
cd nanoBench
make kernel

To load the kernel module, run:

sudo insmod kernel/nb.ko # this is necessary after every reboot

Usage Examples

The recommended way for using nanoBench is with the wrapper scripts nanoBench.sh (for the user-space variant) and kernel-nanoBench.sh (for the kernel module). The following examples work with both of these scripts. For the kernel module, we also provide a Python wrapper: kernelNanoBench.py.

For obtaining repeatable results, it can help to disable hyper-threading. This can be done with the disable-HT.sh script.

Example 1: The ADD Instruction

The following command will benchmark the assembler code sequence "ADD RAX, RBX; ADD RBX, RAX" on a Skylake-based system.

sudo ./nanoBench.sh -asm "ADD RAX, RBX; ADD RBX, RAX" -config configs/cfg_Skylake_common.txt

It will produce an output similar to the following.

CORE_CYCLES: 2.00
INST_RETIRED: 2.00
UOPS_ISSUED: 2.00
UOPS_EXECUTED: 2.00
UOPS_DISPATCHED_PORT.PORT_0: 0.49
UOPS_DISPATCHED_PORT.PORT_1: 0.50
UOPS_DISPATCHED_PORT.PORT_2: 0.00
UOPS_DISPATCHED_PORT.PORT_3: 0.00
UOPS_DISPATCHED_PORT.PORT_4: 0.00
UOPS_DISPATCHED_PORT.PORT_5: 0.50
UOPS_DISPATCHED_PORT.PORT_6: 0.51
UOPS_DISPATCHED_PORT.PORT_7: 0.00
...

The tool will unroll the assembler code multiple times, i.e., it will create multiple copies of it. The results are averages per copy of the assembler code for multiple runs of the entire generated code sequence.

The config file contains the required information for configuring the programmable performance counters with the desired events. We provide example configuration files for recent Intel and AMD microarchitectures in the config folder.

The assembler code sequence may use and modify any general-purpose or vector registers (unless the -loop or -no_mem options are used), including the stack pointer. There is no need to restore the registers to their original values at the end.

R14, RDI, RSI, RSP, and RBP are initialized with addresses in the middle of dedicated memory areas (of 1 MB each), that can be freely modified by the assembler code. When using the kernel module, the size of the memory area that R14 points to can be increased using the set-R14-size.sh script; more details on this can be found here.

All other registers have initially undefined values. They can, however, be initialized as shown in the following example.

Example 2: Load Latency

sudo ./nanoBench.sh -asm_init "MOV RAX, R14; SUB RAX, 8; MOV [RAX], RAX" -asm "MOV RAX, [RAX]" -config configs/cfg_Skylake_common.txt

The asm-init code is executed once in the beginning. It first sets RAX to R14-8 (thus, RAX now contains a valid memory address), and then sets the memory at address RAX to its own address. Then, the asm code is executed repeatedly. This code loads the value at the address in RAX into RAX. Thus, the execution time of this instruction corresponds to the L1 data cache latency.

We will get an output similar to the following.

CORE_CYCLES: 4.00
INST_RETIRED: 1.00
UOPS_ISSUED.ANY: 1.00
UOPS_EXECUTED.THREAD: 1.00
UOPS_DISPATCHED_PORT.PORT_0: 0.00
UOPS_DISPATCHED_PORT.PORT_1: 0.00
UOPS_DISPATCHED_PORT.PORT_2: 0.50
UOPS_DISPATCHED_PORT.PORT_3: 0.50
...
MEM_LOAD_RETIRED.L1_HIT: 1.00
MEM_LOAD_RETIRED.L1_MISS: 0.00
...

Generated Code

We will now take a look behind the scenes at the code that nanoBench generates for evaluating a microbenchmark.

int run(code, code_init, local_unroll_count):
    int measurements[n_measurements]

    for i=-warm_up_count to n_measurements
        save_regs
        code_init
        m1 = read_perf_ctrs // stores results in memory, does not modify registers
        code_late_init
        for j=0 to loop_count // this line is omitted if loop_count=0
            code // (copy #1)
            code // (copy #2)
             ⋮
            code // (copy #local_unroll_count)
        m2 = read_perf_ctrs
        restore_regs
        if i >= 0: // ignore warm-up runs
            measurements[i] = m2 - m1

    return agg(measurements) // apply selected aggregate function

run(...) is executed twice: The first time with local_unroll_count = unroll_count, and the second time with local_unroll_count = 2 * unroll_count. If the -basic_mode options is used, the first execution is with no instructions between m1 = read_perf_ctrs and m2 = read_perf_ctrs, and the second with local_unroll_count = unroll_count.

The result that is finally reported by nanoBench is the difference between these two executions divided by max(loop_count * unroll_count, unroll_count).

Before the first execution of run(...), the performance counters are configured according to the event specifications in the -config file. If this file contains more events than there are programmable performance counters available, run(...) is executed multiple times with different performance counter configurations.

Command-line Options

Both nanoBench.sh and kernel-nanoBench.sh support the following command-line parameters. All parameters are optional. Parameter names may be abbreviated if the abbreviation is unique (e.g., -l may be used instead of -loop_count).

Option	Description
`-asm <code>`	Assembler code sequence (in Intel syntax¹) containing the code to be benchmarked.
`-asm_init <code>`	Assembler code sequence (in Intel syntax¹) that is executed once in the beginning of every benchmark run.
`-asm_late_init <code>`	Assembler code sequence (in Intel syntax¹) that is executed once immediately before the code to be benchmarked.
`-asm_one_time_init <code>`	Assembler code sequence (in Intel syntax¹) that is executed once before the first benchmark run.
`-code <filename>`	A binary file containing the code to be benchmarked as raw x86 machine code. This option cannot be used together with `-asm`.
`-code_init <filename>`	A binary file containing code to be executed once in the beginning of every benchmark run. This option cannot be used together with `-asm_init`.
`-code_late_init <filename>`	A binary file containing code to be executed once immediately before the code to be benchmarked. This option cannot be used together with `-asm_late_init`.
`-code_one_time_init <code>`	A binary file containing code to be executed once before the first benchmark run. This option cannot be used together with `-asm_one_time_init`.
`-config <file>`	File with performance counter event specifications. Details are described below.
`-fixed_counters`	Reads the fixed-function performance counters.
`-n_measurements <n>`	Number of times the measurements are repeated. `[Default: n=10]`
`-unroll_count <n>`	Number of copies of the benchmark code inside the inner loop. `[Default: n=1000]`
`-loop_count <n>`	Number of iterations of the inner loop. If n>0, the code to be benchmarked must not modify R15, as this register contains the loop counter. If n=0, the instructions for the loop are omitted; the loop body is then executed once. `[Default: n=0]`
`-warm_up_count <n>`	Number of runs of the generated benchmark code sequence (in each invocation of `run(...)`) before the first measurement result gets recorded . This can, for example, be useful for excluding outliers due to cold caches. `[Default: n=5]`
`-initial_warm_up_count <n>`	Number of runs of the benchmark code sequence before the first invocation of `run(...)`. This can be useful for benchmarking instructions that require a warm-up period before they can execute at full speed, like AVX2 instructions on some microarchitectures. `[Default: n=0]`
`-alignment_offset <n>`	By default, the code to be benchmarked is aligned to 64 bytes. This parameter allows to specify an additional offset. `[Default: n=0]`
`-avg`	Selects the arithmetic mean (excluding the top and bottom 20% of the values) as the aggregate function. `[This is the default]`
`-median`	Selects the median as the aggregate function.
`-min`	Selects the minimum as the aggregate function.
`-max`	Selects the maximum as the aggregate function.
`-basic_mode`	The effect of this option is described in the Generated Code section.
`-no_mem`	If this option is enabled, the code for `read_perf_ctrs` does not make any memory accesses and stores all performance counter values in registers. This can, for example, be useful for benchmarks that require that the state of the data caches does not change after the execution of `code_init`. If this option is used, the code to be benchmarked must not modify registers R8-R11 (Intel) and R8-R13 (AMD). Furthermore, `read_perf_ctrs` will modify RAX, RCX, and RDX.
`-no_normalization`	If this option is enabled, the measurement results are not divided by the number of repetitions.
`-remove_empty_events`	If this option is enabled, the output does not contain events that did not occur.
`-df`	If this option is enabled, the front-end buffers are drained after `code_init`, after `code_late_init`, and after the last instance of `code` by executing an lfence, followed by a long sequence of 1-Byte `NOP` instructions, followed by a long sequence of 15-Byte `NOP` instructions.
`-cpu <n>`	Pins the measurement thread to CPU n. `[Default: Pin the thread to the CPU it is currently running on.]`
`-verbose`	Outputs the results of all performance counter readings. In the user-space version, the results are printed to stdout. The output of the kernel module can be accessed using `dmesg`.

¹ As an extension, the tool also supports statements of the form |n (with 1≤n≤15) that are translated to n-byte NOPs.

The following parameters are only supported by nanoBench.sh.

Option	Description
`-usr <n>`	If n=1, performance events are counted when the processor is operating at a privilege level greater than 0. `[Default: n=1]`
`-os <n>`	If n=1, performance events are counted when the processor is operating at privilege level 0. `[Default: n=0]`
`-debug`	Enables the debug mode (see below).

The following parameter is only supported by kernel-nanoBench.sh.

Option	Description
`-msr_config <file>`	File with performance counter event specifications for counters that can only be read with the `RDMSR` instruction, such as uncore counters. Details are described below.

Cycle-by-Cycle Measurements

The cycleByCycle.py script provides the option to perform cycle-by-cycle measurements on recent Intel CPUs. This is achieved by enabling the Freeze_Perfmon_On_PMI feature, by setting the value of the core cycles counter to N cycles below overflow, and by repeating the measurements multiple times with different values for N. This approach is based on Brandon Falk's Sushi Roll technique.

As an example, the script can be used as follows.

sudo ./cycleByCycle.py -asm "MOVQ XMM0, RAX; MOVQ RAX, XMM0" -config configs/cfg_Skylake_common.txt -unroll 10

cycleByCycle.py supports mostly the same options as kernel-nanoBench.sh, with the following exceptions. The -fixed_counters and -msr_config options are not available. The -basic_mode, -df, and -no_normalization options are used by default. The default for the -unroll_count parameter is 1, and the default aggregate function is the median.

cycleByCycle.py supports the following additional parameters.

Option	Description
`-html <filename>`	Generates an HTML file with a graphical representation of the measurement data. The filename is optional. `[Default: graph.html]`
`-csv <filename>`	Generates a CSV file that contains the measurement data. The filename is optional. `[Default: stdout]`
`-end_to_end`	By default, `cycleByCycle.py` tries to remove the overhead that comes from the instructions that enable/disable the performance counters, and from the instructions that drain the front end before/after the code of the benchmark is executed. However, this does not always work properly. In such cases, the `-end_to_end` option can be used; with this option, the output includes all of the overhead.

Performance Counter Config Files

We provide provide performance counter configuration files (for counters that can be read with the RDPMC instruction) for most recent Intel and AMD CPUs in the configs folder. These files can be adapted/reduced to the events you are interested in.

The format of the entries in the configuration files is

EvtSel.UMASK(.CMSK=...)(.AnyT)(.EDG)(.INV)(.TakenAlone)(.CTR=...)(.MSR_3F6H=...)(.MSR_PF=...)(.MSR_RSP0=...)(.MSR_RSP1=...) Name

You can find details on the meanings of the different parts of the entries in chapter 18 of Intel's System Programming Guide and at https://download.01.org/perfmon/readme.txt.

MSR Performance Counter Config Files

Some performance counters, such as the uncore counters or the RAPL counters on Intel CPUs, cannot be read with the RDPMC instruction, but only with the RDMSR instruction. The entries in the corresponding configuration files have the following format:

msr_...=...(.msr_...=...)* msr_... Name

For example, the line

msr_0xE01=0x20000000.msr_700=0x408F34 msr_706 LLC_LOOKUP_CBO_0

can be used to count the number of last-level cache lookups in C-Box 0 on a Skylake system. Details on this can be found in Intel's uncore performance monitoring reference manuals, e.g., here.

Pausing Performance Counting

If the -no_mem option is used, nanoBench provides a feature to temporarily pause performance counting (however, this feature is not available for cycle-by-cycle measurements). This is enabled by including the magic byte sequences 0xF0B513B1C2813F04 (for stopping the counters), and 0xE0B513B1C2813F04 (for restarting them) in the code of the microbenchmark.

Using this feature incurs a certain timing overhead that will be included in the measurement results. It is therefore, in particular, useful for microbenchmarks that do not measure the time, but e.g., cache hits or misses, such as the microbenchmarks generated by the tools in tools/CacheAnalyzer.

Debug Mode

If the debug mode is enabled, the generated code contains a breakpoint right before the line m2 = read_perf_ctrs, and nanoBench is run using gdb. This makes it possible to analyze the effect of the code to be benchmarked on registers and on the memory. The command info all-registers can, for example, be used to display the current values of all registers.

Supported Platforms

nanoBench should work with all Intel processors supporting architectural performance monitoring version ≥ 2, as well as with AMD Family 17h processors. Cycle-by-cycle measurements are only available on Intel CPUs with at least four programmable performance counters.

The code was developed and tested using Ubuntu 18.04 and 20.04.

vsrinivas/nanoBench