Vulten

A Vulkan PluggableDevice for Tensorflow

Compatibility

It should hopefully work with any Vulkan 1.2 complient device.

Ops / kernels

• Relu
• ReluGrad
• SoftMax
• BiasAdd
• BiasAddGrad
• MatMul
• AssignAddVariable
• AssignSubVariable
• ReadVariableOp
• Identity
• IdentityN
• Pow
• ResourceApplyAdam
• Cast
• Mul
• Add
• AddV2
• Sub
• Div
• DivNoNan
• AssignVariable
• Sum
• Addn
• Exp
• Sqrt

Example

import tensorflow as tf
import numpy as np

tf.config.run_functions_eagerly(False)

batch    = 1
height    = 512
width    = 512
channels = 3
tensor = tf.random.normal((batch*height*width*channels,), dtype=tf.float32)
tensor = tf.reshape(tensor, (batch, height, width, channels))

with tf.device('VULK:0'):
    tensorRelu = tf.nn.relu(tensor)

Env Variables

• VULTEN_DUMP_SPV=(true/false)
• VULTEN_DISABLE_FLOAT64=(true/false)
• VULTEN_DISABLE_FLOAT16=(true/false)
• VULTEN_DISABLE_INT64=(true/false)
• VULTEN_DISABLE_INT16=(true/false)
• VULTEN_DISABLE_INT8=(true/false)

Build dependencies

• Python 3.10 with venv
• Vulkan SDK

Build instructions

1. Run ./scripts/create_venv.sh to create venv with Tensorflow and other dependencies needed
2. cmake -Bbuild -DCMAKE_BUILD_TYPE=Debug . or cmake -Bbuild -DCMAKE_BUILD_TYPE=Release .
3. cmake --build build/
4. ./scripts/package_wheel.sh builds .whl and installs it in the venv

FAQ

• Is it fast?
  • Nope not enough ops are implmented so it spends ~90% of the time transfering to and from host.