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Data Compression as a CPU Benchmark

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Article from ADMIN 66/2021
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Data compression is a more realistic compute benchmark than number crunching.

At the Dragon Propulsion Laboratory, we have long been looking for a meaningful CPU benchmark, beyond pure computational muscle displays and those architecture-bound demonstrations of number-crunching prowess usually favored by chip vendors. We have long relied on convenient load generators like stress [1] and its modern descendant stress-ng [2], but putting load on the system and summing its performance in a few numbers are not really the same thing: The latter helps compare systems, whereas the former helps test them. I think the search is finally over, and I am settling on data compression as a more realistic compute benchmark that does not look like a stress exercise for a vintage math coprocessor or a GPU.

Comparing systems should always involve a real workload, and comparing an ARM with an x86 system on the grounds of how fast it can compress data feels more truthful than doing so on pure disjoint CPU operations. Of course, if more information is available, it should be used by testing with the exact workload, but otherwise this choice represents a sensible default.

Enter LZMA

The Lempel-Ziv-Markov chain algorithm (LZMA) [3] is a dictionary-based, lossless compression algorithm in use with the 7-Zip archiver [4]. Demonstrating higher compression ratios than the original LZ77 [5] algorithm, it is generally expected to have comparable decompression performance. More important to the purpose, 7-Zip's author is very methodical with his performance testing, providing a reference library of results for many CPU types [6], and prebuilt binaries of the tool exist for both Linux and Windows. A sampling of the results library available online is the benchmark for the recent Apple M1 processor, captured in Figure 1 [7], including both test results and CPU architecture notes.

Figure 1: Processor-specific notes in the 7-Zip benchmark library – in this example, results for the Apple M1 CPU.

Per my usual custom, I test on the latest Ubuntu LTS, 20.04 "Focal Fossa," with 7-Zip installed from the Universe repository:

$ sudo apt install p7zip-full

After completing the install, you have access to a straightforward benchmark requiring no setup or configuration through the single command 7z b – in this variation, MIPS results are normalized against a "standard" Intel Core 2. Running the test on a single virtual CPU (vCPU) Digital Ocean droplet in the NYC1 availability zone yielded the results found in Listing 1. The results size this core at about 3 billion instructions per second (see the MIPS rating). On a multicore processor, the benchmark would repeat continuing to double the cores in use up to the maximum allowable number, as for the Apple M1 [7] example with eight cores in Listing 2. The results there approach 50 billion instructions per second.

Listing 1

7z b Output

7-Zip [64] 16.02 : Copyright (c) 1999-2016 Igor Pavlov : 2016-05-21
p7zip Version 16.02 (locale=C.UTF-8,Utf16=on,HugeFiles=on,64 bits,1 CPU Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz (50654),ASM,AES-NI)
Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz (50654)
CPU Freq: - - - - - - - - -
RAM size:    1987 MB,  # CPU hardware threads:   1
RAM usage:    435 MB,  # Benchmark threads:      1
                       Compressing  |                  Decompressing
Dict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating
         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS
22:       3062   100   2987   2979  |      35411   100   3028   3023
23:       2733   100   2787   2785  |      34100   100   2954   2952
24:       2482    99   2702   2669  |      33606   100   2957   2950
25:       2312    99   2657   2640  |      31616   100   2822   2814
----------------------------------  | ------------------------------
Avr:              99   2783   2768  |              100   2940   2935
Tot:             100   2862   2852

Listing 2

7z b Apple M1 Output

7-Zip (z) 21.03 beta (arm64) : Copyright (c) 1999-2021 Igor Pavlov : 2021-07-20
 64-bit arm_v:8 locale=en_US.UTF-8 Threads:8, ASM
Compiler: Apple LLVM 12.0.5 (clang-1205.0.22.9) GCC 4.2.1 CLANG 12.0
Darwin : 20.4.0 : Darwin Kernel Version 20.4.0:
PageSize:16KB
Apple M1 8C8T
RAM size:   16384 MB,  # CPU hardware threads:   8
RAM usage:   1779 MB,  # Benchmark threads:      8
                       Compressing  |                  Decompressing
Dict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating
         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS
22:      51020   750   6559  49633  |     538251   795   5762  45898
23:      46106   727   6402  46977  |     529572   795   5757  45809
24:      45006   749   6452  48391  |     515399   788   5722  45221
25:      44111   759   6616  50365  |     505839   793   5664  45009
----------------------------------  | ------------------------------
Avr:     46561   747   6507  48841  |     522265   792   5726  45484
Tot:             770   6117  47163

Infos

  1. stress: https://githubmemory.com/repo/resurrecting-open-source-projects/stress
  2. stress-ng: https://github.com/ColinIanKing/stress-ng
  3. LZMA: https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Markov_chain_algorithm
  4. 7-Zip: https://www.7-zip.org/
  5. Ziv, Jacob, and Abraham Lempel. A Universal Algorithm for Sequential Data Compression. IEEE Transactions on Information Theory, May 1977, 23:3
  6. 7-Zip CPU benchmark library: https://www.7-cpu.com/
  7. Apple M1 7z benchmark results: https://www.7-cpu.com/cpu/Apple_M1.html

The Author

Federico Lucifredi (@0xf2) is the Product Management Director for Ceph Storage at Red Hat, formerly the Ubuntu Server Product Manager at Canonical, and the Linux "Systems Management Czar" at SUSE. He enjoys arcane hardware issues and shell-scripting mysteries and takes his McFlurry shaken, not stirred. You can read more from him in the O'Reilly title AWS System Administration .

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