CoreMark®-PRO is a comprehensive, advanced processor benchmark that works with and enhances the market-proven industry-standard EEMBC CoreMark® benchmark. While CoreMark stresses the CPU pipeline, CoreMark-PRO tests the entire processor, adding comprehensive support for multicore technology, a combination of integer and floating-point workloads, and data sets for utilizing larger memory subsystems. Together, EEMBC CoreMark and CoreMark-PRO provide a standard benchmark covering the spectrum from low-end microcontrollers to high-performance computing processors.
The EEMBC CoreMark-PRO benchmark contains five prevalent integer workloads and four popular floating-point workloads.
The integer workloads include:
- JPEG compression
- ZIP compression
- XML parsing
- SHA-256 Secure Hash Algorithm
- A more memory-intensive version of the original CoreMark
The floating-point workloads include:
- Radix-2 Fast Fourier Transform (FFT)
- Gaussian elimination with partial pivoting derived from LINPACK
- A simple neural-net
- A greatly improved version of the Livermore loops benchmark using the following 24 FORTRAN kernels converted to C (all of these reported as a single score of the
loops.cworkload). The standard Livermore loops include:- Kernel 1 -- hydro fragment
- Kernel 2 -- ICCG excerpt (Incomplete Cholesky Conjugate Gradient)
- Kernel 3 -- inner product
- Kernel 4 -- banded linear equations
- Kernel 5 -- tri-diagonal elimination, below diagonal
- Kernel 6 -- general linear recurrence equations
- Kernel 7 -- equation of state fragment
- Kernel 8 -- ADI integration
- Kernel 9 -- integrate predictors
- Kernel 10 -- difference predictors
- Kernel 11 -- first sum
- Kernel 12 -- first difference
- Kernel 13 -- 2-D PIC (Particle In Cell)
- Kernel 14 -- 1-D PIC (pticle In Cell)
- Kernel 15 -- Casual Fortran.
- Kernel 16 -- Monte Carlo search loop
- Kernel 17 -- implicit, conditional computation
- Kernel 18 -- 2-D explicit hydrodynamics fragment
- Kernel 19 -- general linear recurrence equations
- Kernel 20 -- Discrete ordinates transport, conditional recurrence on xx
- Kernel 21 -- matrix*matrix product
- Kernel 22 -- Planckian distribution
- Kernel 23 -- 2-D implicit hydrodynamics fragment
- Kernel 24 -- find location of first minimum in array
The CoreMark-PRO score is a weighted geometric mean of each workload, as describe on page 12 of the provided PDF document.
Build the benchmark using the make command and specificying a target architecture with TARGET=. Accomodations for custom targets and toolchains are placed in the util/make folder. To compile for Linux and the gcc64 toolchain, use this command:
% make TARGET=linux64 build
This will include the util/make/linux64.mak file, which in turn includes the gcc64.mak file for the toolchain. When finished, nine executables are saved in builds/linux64/gcc64/bin folder. These are binaries used by the test.
The command:
% make TARGET=linux64 XCMD='-c4' certify-all
...runs all of the nine tests (with four contexts), collects their output scores, and processes them through a Perl script to generate the final CoreMark-PRO score, like so:
WORKLOAD RESULTS TABLE
MultiCore SingleCore
Workload Name (iter/s) (iter/s) Scaling
----------------------------------------------- ---------- ---------- ----------
cjpeg-rose7-preset 555.56 156.25 3.56
core 4.87 1.30 3.75
linear_alg-mid-100x100-sp 1428.57 409.84 3.49
loops-all-mid-10k-sp 22.56 6.25 3.61
nnet_test 33.22 10.56 3.15
parser-125k 70.18 19.23 3.65
radix2-big-64k 1666.67 453.72 3.67
sha-test 588.24 172.41 3.41
zip-test 500.00 142.86 3.50
MARK RESULTS TABLE
Mark Name MultiCore SingleCore Scaling
----------------------------------------------- ---------- ---------- ----------
CoreMark-PRO 19183.84 5439.59 3.53
This will run all nine tests twice, once with one context and once with a user-defined number of contexts, in this case four, and then generate the scaling between the two configurations. Please refer to the documentation for explanations of how to change the number of contexts and workers.
The benchmark utilizes EEMBC's Multi-Instance Test Harness, or MITH. Found in the mith folder, the test harness consists of high-level functions for launching the tests, and a low-level abstraction layer (in the al folder) for interfacing with the hardware or operating system. The file th_al.c in the al/src folder is the only place modifications are needed to port the benchmark to new hardware. In fact, changing any other source files invalidates the CoreMark-PRO score.
Out of the box, the MITH abstraction layer is configured to work with the POSIX pthread architecture on Linux, but any thread scheduling system that can be represented through the MITH abstraction layer is valid (including no threading on baremetal). The MITH harness provieds a mith_main function, and the actual main functions are provided in the workload areas.
The example above was run from a Linux CLI, where it is possible to invoke each binary in simple succession via the Makefile and collect scores for analysis by the Perl script. Non-Linux targets (e.g., baremetal) are more complex to run, as each binary needs to be downloaded to the hardware manually and the individual results collected from a remote debugger console by retargeting the al_printf function. The computation for the CoreMark-PRO score is described in the included PDF documentation.
As stated above, each workload compiles to a single binary. The workloads in the workloads folder contain a top-level C-file that instantiates the test harness. A workload consists of one or more benchmark kernels (stored in the kernels folder), and a dataset (see NOTE below). For example, the binary loops-all-mid-10k-sp.exe is compiled from workloads/loops-all-mid-10k-sp. This workload invokes the Livermore Loops kernel from benchmarks/loops/ and configures it to use the ref-sp/10k.c file. This file includes parameters for constructing a 10 KB dataset, as well as the reference data results to compare against after the benchmark completes. Floating point benchmarks check for accuracy by checking a minimum number of bits that are allowed to differ (this is of greater concern in other benchmarks like EEMBC's FPMark, which stresses single- and double-precision performance). Other benchmark kernels contain just the input dataset and no reference, such as the JPEG workload.
NOTE: In CoreMark-PRO, the mapping is 1:1, each workload invokes one kernel. Other MITH-based benchmarks from EEMBC, such as AutoBench 2.0, multiple kernels are arranged in different configurations in each workload.
The following metrics were captured under Ubuntu 20.04 running on an Intel(R) Core(TM) i5-1035G4 CPU using GCC 9.3.0 (with -O2). The static footprint was taken with size and the dynamic peak with valgrind --stats=yes --profile-heap=yes --tool=massif --stacks=yes --time-unit=B subtool. Values are in bytes.
| Component | text | data | bss | dec | massif peak B |
|---|---|---|---|---|---|
| cjpeg-rose7-preset.exe | 112,292 | 268,576 | 208 | 381,076 | 141,488 |
| core.exe | 70,356 | 2,240 | 2,448 | 75,044 | 12,496 |
| linear_alg-mid-100x100-sp.exe | 75,277 | 3,112 | 1,424 | 79,813 | 67,656 |
| loops-all-mid-10k-sp.exe | 91,391 | 4,696 | 3,664 | 99,751 | 3,427,184 |
| nnet_test.exe | 73,739 | 3,568 | 40,272 | 117,579 | 50,528 |
| parser-125k.exe | 90,415 | 2,272 | 208 | 92,895 | 1,043,032 |
| radix2-big-64k.exe | 1,449,387 | 1,904 | 688 | 1,451,979 | 1,580,504 |
| sha-test.exe | 80,717 | 2,184 | 208 | 83,109 | 1,052,272 |
| zip-test.exe | 135,245 | 2,776 | 208 | 138,229 | 3,420,864 |
Please refer to the PDF user guide located in the docs folder of this repository for more details.
More info may be found at the EEMBC CoreMark-PRO website.
What is and is not allowed.
- Each workload must run for at least 1000 times the minimum timer resolution. For example, on a 10 ms timer tick based system, each workload must run for at least 10 seconds.
- To report results, the build target
certify-allmust be used or that process must be followed ifmakeis not usable (e.g. via embedded debugger runs); each workload must report no errors when run with-v1. - All workloads within CoreMark-Pro must be compiled with the same flags and linked with the same flags. These must be disclosed and/or reported with any publication of CoreMark-Pro scores.
- You may change the number of iterations.
- You may change toolchain and build/load/run options.
- You may change the implementation of porting files under mith/al sub tree.
- You may change makefiles or using IDE projects.
- Profile guided optimizations are allowed on base run; if used, they must be used for all workloads.
- You may not change the source file under benchmarks or workloads folders.
NEW! A baremetal porting guide has been added to the doc directory of this repository.
The MITH hardare abstraction layer is defined in mith/al/src. These files contain any low-level functions needed by the benchmark. The MITH framework is used for a number of benchmarks, so not all options are relevant to or used by CoreMark-PRO.
The provided implementaiton was tested on 32- and 64-bit Linux distributions, as well as Cygwin. Since the datasets are loaded implicitly as C-structures, file I/O is not used. The only major modification likely needed for an embedded port is how pthreads are implemented. Choices are:
- Provide a POSIX thread library
- Switch to single-thread mode by using the reference
al_single.cinstead ofal_smp.c - Implement the functions
al_smp.cusing the target platform's threading SDK
There's no standard flash downloader or response extractor included because every tool chain or IDE behaves differently in this regard. One easy method is to load each compiled firmware image through an IDE debugger and extract the results either by redirecting the th_printf function, or simply reading the IDE debugger output assuming vsprintf is redirected to the IDE or console via the debuggger link. The computation of the CoreMark-PRO score is described on page 12 of the provided PDF user's guide.
The makefiles automate macro setting and data set inclusion. When not using the makefiles, it can be tricky to determine the proper macro definitions; be sure to set the following macros and use these datasets:
| Component | Macros | File or directory to include |
|---|---|---|
| cjpeg-rose7-preset | SELECT_PRESET_ID=1, USE_PRESET | consumer_v2/cjpeg/*.cconsumer_v2/cjpeg/data/Rose256_bmp.c |
| core | core/core_*.c |
|
| linear_alg-mid-100x100-sp | USE_FP32=1 | fp/linpack/linpack.cfp/linpack/ref/inputs_f32.c |
| loops-all-mid-10k-sp | USE_FP32=1 | fp/loops/loops.cfp/loops/ref-sp/*.c |
| nnet_test | USE_FP64=1 | fp/nnet/nnet.cfp/nnet/ref/*.c |
| parser-125k | darkmark/parser/*.c |
|
| radix2-big-64k | USE_FP64=1 | fp/fft_radix2/fft_radix2.cfp/fft_radix2/ref/*.c |
| sha-test | darkmark/sha/*.c |
|
| zip-test | MITH_MEMORY_ONLY_VERSION, ZLIB_COMPAT_ALL, ZLIB_ANSI | darkmark/zip/zip_darkmark.cdarkmark/zip/zlib-1.2.8/*.c but exclude gzread.c and gzwrite.c. |
Each workload defines a main() that takes argc and argv. In order to run the performance measurement, the benchmark requires the input argument "-v0" (turn off default validation mode), and to follow the run rules, iterations might need to be changed with the "-i" option. Since these options are provided via argv, this may cause problems. If your debugger allows semihosting, you can provide these options through an argument string. If your compiler can rename the entrypoint from main() to something else, you can create a wrapper that calls the workload main() with an argument string, e.g. char *argv[] = { "-v0", "-i100" }; .... If neither options are available, you will need to alter the workload main() function to be main(void) and define your own argc and argv immediately prior to the call to al_main().
You are allowed to alter th_al.c. It is expected that the platform startup and init code will need to go in al_main(), as well as porting the clock mechanism defined by the al_signal_*() functions. Often these are simply replaced with an interrupt timer (rather than an RTC) at 1ms resolution. If the timer is not 1ms, you will need to set the CLOCKS_PER_SEC defines in th_al.c.
The final score is a geometric mean of the components divided by a reference platform score and scaled. If CoreMark-PRO is run on the host system, a PERL script will automatically perform this computation. If run on a remote target, it must be done manually. First collect the iterations-per-second for each of the components. Then divide each component by the reference score shown below, then multiply each term by the scale factor, and take the geometric mean of the resulting values. Finally multiply by 1000.
| Component | Scale Factor | Reference Score |
|---|---|---|
| cjpeg-rose7-preset.exe | 1 | 40.3438 |
| core.exe | 10000 | 2855 |
| linear_alg-mid-100x100-sp.exe | 1 | 38.5624 |
| loops-all-mid-10k-sp.exe | 1 | 0.87959 |
| nnet_test.exe | 1 | 1.45853 |
| parser-125k.exe | 1 | 4.81116 |
| radix2-big-64k.exe | 1 | 99.6587 |
| sha-test.exe | 1 | 48.5201 |
| zip-test.exe | 1 | 21.3618 |
Final Score = GeoMean(s0/r0 * x0, s1/r1 * x1, ..., sN/rN * xN) * 1000
Where sN, rN and xN refer to the current score, reference score and scale factor, respectively, for each of the N components.
CoreMark-PRO results can be submitted on the web. Open a web browser and go to the submission page. After registering an account you may enter a score.
- As stated in the license, a "Commercial COREMARK-PRO License" from EEMBC is required for Licensee to disclose, reference, or publish test results generated by COREMARK-PRO in Licensee’s marketing of any of Licensee’s commercially‐available, product‐related materials, including, but not limited to product briefs, website, product brochures, product datasheets, or any white paper or article made available for public consumption. (This does not include academic research or personal use)
- Scores must be uploaded to the EEMBC CoreMark-PRO website before being published in any capacity to ensure run rules were followed.
EEMBC and CoreMark are trademarks of EEMBC. Please refer to the file LICENSE.md for the license associated with this benchmark software.
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