oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative.

To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark onednn.

Performance Metrics

oneDNN 2.1.2

Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU

OpenBenchmarking.org metrics for this test profile configuration based on 28 public results since 13 March 2021 with the latest data as of 1 April 2021.

Additional benchmark metrics will come after OpenBenchmarking.org has collected a sufficient data-set.

Based on OpenBenchmarking.org data, the selected test / test configuration (oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU) has an average run-time of 2 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 0.7%.

Notable Instruction Set Usage

Notable instruction set extensions supported by this test, based on an automatic analysis by the Phoronix Test Suite / OpenBenchmarking.org analytics engine.

This test profile binary relies on the shared libraries libdnnl.so.2, libpthread.so.0, libm.so.6, libgomp.so.1, libc.so.6, libdl.so.2.

Recent Test Results