Ingestion of data for machine learning distributed training
AssigneeIntel Corporation
InventorsVikram Saletore, Yaser Afshar
Life of this patent
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Abstract
Systems and methods include technology that identifies a first shard of shards of training data, where the training data is stored on a storage array, where the training data is divided into shards. The technology stores the first shard onto a first data storage of a first compute node, and copies the first shard from the first data storage of the first compute node onto a second data storage of the first compute node. The technology trains a machine learning model on the first shard stored in the second data storage during a first epoch of a training phase.
Claims20
A first compute node comprising:
- a network controller to communicate with second compute nodes and a storage array, wherein the storage array is to store training data that is divided into shards;
- one or more of a processor implemented in one or more of configurable logic or fixed-functionality logic, or an accelerator implemented in one or more of configurable logic or fixed-functionality logic;
- a first data storage;
- a second data storage;
- and
- a memory including a set of instructions, which when executed by the one or more of the processor or the accelerator, cause the first compute node to:
- store a first shard of the shards onto the first data storage;
- copy the first shard from the first data storage onto the second data storage;
- and
- train a machine learning model on the first shard stored in the first data storage during a first epoch of a training phase.
A semiconductor apparatus, the semiconductor apparatus comprising:
- one or more substrates;
- and
- logic coupled to the one or more substrates, wherein the logic is implemented in one or more of configurable logic or fixed-functionality logic, the logic coupled to the one or more substrates to:
- identify a first shard of shards of training data, wherein the training data is stored on a storage array, wherein the training data is divided into shards;
- store the first shard onto a first data storage of a first compute node;
- copy the first shard from the first data storage of the first compute node onto a second data storage of the first compute node;
- and
- train a machine learning model on the first shard stored in the first data storage during a first epoch of a training phase.
A method comprising:
- identifying a first shard of shards of training data, wherein the training data is stored on a storage array, wherein the training data is divided into shards;
- storing the first shard onto a first data storage of a first compute node;
- copying the first shard from the first data storage of the first compute node onto a second data storage of the first compute node;
- and
- training a machine learning model on the first shard stored in the first data storage during a first epoch of a training phase.
Dependencies are inferred from the claim text.