ZigZag - Deep Learning Hardware Design Space Exploration
This repository presents the novel version of our tried-and-tested hardware Architecture-Mapping Design Space Exploration (DSE) Framework for Deep Learning (DL) accelerators. ZigZag bridges the gap between algorithmic DL decisions and their acceleration cost on specialized accelerators through a fast and accurate hardware cost estimation.
Classes | Variables
zigzag.opt.salsa.engine Namespace Reference

Classes

class  SalsaEngine
 Class that handles optimization of temporal mapping given a: More...
 

Variables

 logger = logging.getLogger(__name__)
 

Detailed Description

Title: engine.py Description: This file contains the engine class that handles the optimization of temporal mapping of SALSA.

Date: 02.01.2023

Copyright (C) 2020 ETH Zurich and University of Bologna.

Author: Victor Jung, ETH Zurich

SPDX-License-Identifier: Apache-2.0

Licensed under the Apache License, Version 2.0 (the License); you may not use this file except in compliance with the License. You may obtain a copy of the License at

www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an AS IS BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Variable Documentation

◆ logger

logger = logging.getLogger(__name__)