.. ****************************************************************************** .. * Copyright 2021 Intel Corporation .. * .. * 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 .. * .. * http://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. .. *******************************************************************************/ .. _memory_requirements: ################### Memory Requirements ################### By default, algorithms in |intelex| run in multi-thread mode, which uses all available threads. This may lead to optimized algorithms consuming more RAM than the corresponding stock scikit-learn algorithms. .. list-table:: :widths: 10 30 30 :header-rows: 1 :align: left * - Algorithm - Single-thread mode - Multi-thread mode * - SVM - Both Scikit-learn and |intelex| consume approximately the same amount of RAM. - In |intelex|, an algorithm with ``N`` threads will consume ``N`` times more RAM. Memory consumption on GPU ------------------------- In all |intelex| algorithms with GPU support, computations run on device memory. The device memory must be large enough to store a copy of the entire dataset. Additional device memory may also be required for internal arrays used in computation.