Not utilising AVX2 instructions after compilation from sources

System information

• OS Platform and Distribution: Linux Ubuntu 20.04
• TensorFlow installed from (source or binary): built via "mvn install"
• TensorFlow version: 2.3 (using 0.2.0-SNAPSHOT)
• Python version: 3.8.2
• Bazel version (if compiling from source): 3.4.1
• GCC/Compiler version (if compiling from source): 9.3.0

Problem:

I have been using TF 1.15 from original java TF repository

<dependency>
    <groupId>org.tensorflow</groupId>
    <artifactId>tensorflow</artifactId>
    <version>1.15.0</version>
</dependency>

which gave me this output:

I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2494460000 Hz
I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f77250299d0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version

so found out this repo, made environment to be able to build TF from sources, ran mvn install command which, I would assume, compiled TF on my specific platform. Using dependencies in my project:

<dependency>
    <groupId>org.tensorflow</groupId>
    <artifactId>tensorflow-core-api</artifactId>
    <version>0.2.0-SNAPSHOT</version>
</dependency>
<dependency>
    <groupId>org.tensorflow</groupId>
    <artifactId>tensorflow-core-api</artifactId>
    <version>0.2.0-SNAPSHOT</version>
    <classifier>linux-x86_64</classifier>
</dependency>

getting output:

Warning: Could not load Loader: java.lang.UnsatisfiedLinkError: no jnijavacpp in java.library.path: [/usr/java/packages/lib, /usr/lib64, /lib64, /lib, /usr/lib]
Warning: Could not load Pointer: java.lang.UnsatisfiedLinkError: no jnijavacpp in java.library.path: [/usr/java/packages/lib, /usr/lib64, /lib64, /lib, /usr/lib]
Warning: Could not load BytePointer: java.lang.UnsatisfiedLinkError: no jnijavacpp in java.library.path: [/usr/java/packages/lib, /usr/lib64, /lib64, /lib, /usr/lib]
I external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Warning: Could not load PointerPointer: java.lang.UnsatisfiedLinkError: no jnijavacpp in java.library.path: [/usr/java/packages/lib, /usr/lib64, /lib64, /lib, /usr/lib]

Everything somehow runs, but throughput is about the same as generic 1.15 version and latency is about 2 times worse than the previous version using the same TF model with V1 behavior enabled. Not sure how to enable AVX2 FMA instructions when TF clearly founds them. I suppose it has something to do about missing jnijavacpp library. Could anyone help me, please?

Thanks

No source files or tests are named. Start by reproducing the Ubuntu 20.04 build with mvn install, then inspect the native library loading warnings and the reported AVX2/FMA message. Done would require identifying why the built Java package does not match the expected performance and documenting or verifying the fix with comparable throughput and latency measurements.