#Distributed Computing
Latest news articles tagged with "Distributed Computing". Follow the timeline of events, related topics, and entities.
Articles (6)
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🇺🇸 Tula: Optimizing Time, Cost, and Generalization in Distributed Large-Batch Training
[USA]
arXiv:2603.18112v1 Announce Type: cross Abstract: Distributed training increases the number of batches processed per iteration either by scaling-out (adding more nodes) or scaling-up (increasing the ...
Related: #Machine Learning, #Training Optimization -
🇺🇸 Deep Randomized Distributed Function Computation (DeepRDFC): Neural Distributed Channel Simulation
[USA]
arXiv:2603.10750v1 Announce Type: cross Abstract: The randomized distributed function computation (RDFC) framework, which unifies many cutting-edge distributed computation and learning applications, ...
Related: #Neural Networks, #Channel Simulation -
🇺🇸 GetBatch: Distributed Multi-Object Retrieval for ML Data Loading
[USA]
arXiv:2602.22434v1 Announce Type: cross Abstract: Machine learning training pipelines consume data in batches. A single training step may require thousands of samples drawn from shards distributed ac...
Related: #Machine Learning, #Data Optimization, #Storage Efficiency -
🇺🇸 veScale-FSDP: Flexible and High-Performance FSDP at Scale
[USA]
arXiv:2602.22437v1 Announce Type: cross Abstract: Fully Sharded Data Parallel (FSDP), also known as ZeRO, is widely used for training large-scale models, featuring its flexibility and minimal intrusi...
Related: #AI Training Optimization, #System Architecture -
🇺🇸 Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling
[USA]
arXiv:2503.04398v4 Announce Type: replace-cross Abstract: Prevailing LLM serving engines employ expert parallelism (EP) to implement multi-device inference of massive MoE models. However, the efficie...
Related: #Machine Learning Optimization, #LLM Efficiency -
🇺🇸 TimelyFreeze: Adaptive Parameter Freezing Mechanism for Pipeline Parallelism
[USA]
arXiv:2602.05754v1 Announce Type: cross Abstract: Pipeline parallelism enables training models that exceed single-device memory, but practical throughput remains limited by pipeline bubbles. Although...
Related: #Artificial Intelligence, #Machine Learning
Key Entities (4)
- Clustered file system (1 news)
- Machine learning (1 news)
- Tula (1 news)
- Distributed computing (1 news)
About the topic: Distributed Computing
The topic "Distributed Computing" aggregates 6+ news articles from various countries.