| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_7fa2a002b2217830b670e2b42f923139 |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F2209-485 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06K9-6257
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F9-4881
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F11-1407
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2148
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F9-461
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T1-60
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T1-20 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F11-14
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F11-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F9-48
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F9-46
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T1-60
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T1-20 |
| filingDate |
2018-04-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate |
2020-06-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_60635f7dc510d3c531f730571568edd6
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d99171783d9186fe3c5246a35fcc0448 |
| publicationDate |
2020-06-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-10698766-B2 |
| titleOfInvention |
Optimization of checkpoint operations for deep learning computing |
| abstract |
Systems and methods are provided to optimize checkpoint operations for deep learning (DL) model training tasks. For example, a distributed DL model training process is executed to train a DL model using multiple accelerator devices residing on one or more server nodes, and a checkpoint operation is performed to generate and store a checkpoint of an intermediate DL model. A checkpoint operation includes compressing a checkpoint of an intermediate DL model stored in memory of a given accelerator device to generate a compressed checkpoint, and scheduling a time to perform a memory copy operation to transfer a copy of the compressed checkpoint from the memory of the given accelerator device to a host system memory. The scheduling is performed based on information regarding bandwidth usage of a communication link to be utilized to transfer the compressed checkpoint to perform the memory copy operation, wherein the memory copy operation is performed at the scheduled time. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022087811-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11546417-B2 |
| priorityDate |
2018-04-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |