bindings

PyTorch Bindings

We provide (so far experimental) bindings to PyTorch. The bindings are specified in bindings.cc, usage examples can be found in example.py.

The bindings provide the three primitives of AdaPS: pull, push, and intent. They further provide a set variant of the push primitive that sets parameter to specific values (instead of adding to the values, as push does).

PyTorch tensors

keys = torch.LongTensor([1,2,3,4])
values = torch.ones((len(keys)*10), dtype=torch.float32)

# pull
kv.push(keys, values)

# push
kv.pull(keys, values)

# set (variant of push)
kv.set(keys, values)

# signal intent and advance clock
kv.intent(keys, 2, 3)
kv.advance_clock()

NumPy arrays

The bindings also accept numpy arrays:

keys = np.array([1,2,3,4])
values = np.ones(len(keys)*10, dtype=np.float32)

# pull
kv.push(keys, values)

# push
kv.pull(keys, values)

# set (variant of push)
kv.set(keys, values)

# signal intent and advance clock
kv.intent(keys, 2, 3)
kv.advance_clock()

Synchronous and asynchronous operations

By default, all operations run synchronously. To run asynchronously, pass async=True to any operation:

kv.pull(keys, values, True)
kv.push(keys, values, True)

In particular, push is often executed asynchronously.

kv.wait() explicitly waits for the execution of a specific operation:

timestamp = kv.pull(keys, values, True)

# do something else

kv.wait(timestamp) # wait for pull to finish

All operations (pull, push, set, and intent) return a timestamp that can be used this way.

Installation

Compile AdaPS with int64 keys (to match PyTorch and NumPy default integer data types) and with the appropriate ABI version, then use setup.py to compile the bindings (see below). Pip PyTorch installations often use the old (pre C++11) ABI. The script lookup_torch_abi.py reads out the ABI version of the installed PyTorch. You can also specify the ABI version manually. To avoid ABI version conflicts with system provided libraries (e.g., boost) for the apps in apps/ (which use system-provided boost), compile the pre-C++ ABI dependencies to a separate path deps_bindings (using DEPS_PATH=$(pwd)/deps_bindings). If you compile the dependencies to another path than deps_bindings you have to modify setup.py.

Make sure that you install PyTorch before you run the installation of AdaPS (below). Otherwise, the ABI read-out will not work (and instead just use the default ABI).

make clean
make ps KEY_TYPE=int64_t CXX11_ABI=$(python bindings/lookup_torch_abi.py) DEPS_PATH=$(pwd)/deps_bindings
cd bindings
python setup.py install --user

If successful, you can now use AdaPS in Python

#!/usr/bin/python
import torch
import adaps

Experimental status

These bindings have an experimental status. If you run into any problems or have questions, please don't hesitate to contact us.