Fixstars Amplify

Fixstars Amplify Annealing Engine

The QUBO solver provided by Fixstars Amplify uses an algorithm based on Simulated Annealing implemented on GPUs.

Tip

A free API token is available upon user registration.

Solver specification:

Client class	amplify.FixstarsClient
Execution parameters	amplify.FixstarsClient.Parameters
Execution result	amplify.FixstarsClient.Result
Execution time	amplify.FixstarsClient.Result.execution_time
API method	REST API (JSON)
API reference	📖 API Reference

	Binary variable	Ising variable	Integer variable	Real variable
Objective function	2nd	-	-	-
Equality constraint	2nd*	-	-	-
Inequality constraint	2nd*	-	-	-

*: must give a penalty function.

Client class:

In addition to the common interface of the client class, it has the following attributes.

Attribute	Data type	Details
compression	bool	Compress the requested data before sending. The default is True; setting it to False will reduce request data compression time, but may increase transmission time.

Configuration example:

from amplify import FixstarsClient
from datetime import timedelta

client = FixstarsClient()

# Set API token
client.token = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"

# Set timeout to 1 second
client.parameters.timeout = timedelta(milliseconds=1000)

# Set the number of GPUs to use to 1
client.parameters.num_gpus = 1

# Get all solutions obtained during the search
client.parameters.outputs.num_outputs = 0

Execution example:

from amplify import Model, VariableGenerator, solve

# Define decision variables and the objective function
g = VariableGenerator()
q = g.array("Binary", 2)
f = q[0] * q[1] + q[0] - q[1] + 1

# Create a model
model = Model(f)

# Run the solver
result = solve(model, client)

Obtain the solver version:

>>> client.version
'v0.8.5-V100'