OpenVKL
OpenVKL is the Intel Open Volume Kernel Library that offers high-performance volume computation kernels and part of the Intel oneAPI rendering toolkit.
To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark openvkl.
Project Site
openvkl.orgSource Repository
github.comTest Created
7 April 2020Last Updated
13 August 2021Test Maintainer
Michael LarabelTest Type
ProcessorAverage Install Time
2 SecondsAverage Run Time
17 Minutes, 49 SecondsAccolades
5k+ DownloadsSupported Platforms
Supported Architectures
** Data based on those opting to upload their test results to OpenBenchmarking.org and users enabling the opt-in anonymous statistics reporting while running benchmarks from an Internet-connected platform.
*** Test profile page view reporting began March 2021.
Data current as of 21 September 2021.
Suites Using This Test
Performance Metrics
Analyze Test Configuration:OpenVKL 0.9
Benchmark: vklBenchmark
OpenBenchmarking.org metrics for this test profile configuration based on 1,328 public results since 7 April 2020 with the latest data as of 2 September 2021.
Below is an overview of the generalized performance for components where there is sufficient statistically significant data based upon user-uploaded results. It is important to keep in mind particularly in the Linux/open-source space there can be vastly different OS configurations, with this overview intended to offer just general guidance as to the performance expectations.
Based on OpenBenchmarking.org data, the selected test / test configuration (OpenVKL 0.9 - Benchmark: vklBenchmark) has an average run-time of 16 minutes. By default this test profile is set to run at least 3 times but may increase if the standard deviation exceeds pre-defined defaults or other calculations deem additional runs necessary for greater statistical accuracy of the result.
Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.4%.
Does It Scale Well With Increasing Cores?
Yes, based on the automated analysis of the collected public benchmark data, this test / test settings does generally scale well with increasing CPU core counts. Data based on publicly available results for this test / test settings, separated by vendor, result divided by the reference CPU clock speed, grouped by matching physical CPU core count, and normalized against the smallest core count tested from each vendor for each CPU having a sufficient number of test samples and statistically significant data.