| Dataset Placement and Data Loading Optimizations for Cloud-Native Deep Learning Workloads | |
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| Author | |
| Abstract | 
   The primary challenge facing cloud-based deep learning systems is the need for efficient orchestration of large-scale datasets with diverse data formats and provisioning of high-performance data loading capabilities. To that end, we present DLCache, a cloud-native dataset management and runtime-aware data-loading solution for deep learning training jobs. DLCache supports the low-latency and high-throughput I/O requirements of DL training jobs using cloud buckets as persistent data storage and a dedicated computation cluster for training. 
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| Year of Publication | 
   2023 
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| Conference Name | 
   IEEE International Symposium on Real-time Computing (ISORC) 
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| Date Published | 
   May 
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| Publisher | 
   IEEE 
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| Conference Location | 
   Nashville, TN 
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| ISBN Number | 
   979-8-3503-3902-4 
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| Accession Number | 
   23517989 
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| URL | 
   https://ieeexplore.ieee.org/document/10196902 
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| DOI | 
   10.1109/ISORC58943.2023.00023 
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