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cs.DC2024
Pipette: Automatic Fine-grained Large Language Model Training Configurator for Real-World Clusters
Jinkyu Yim, Jaeyong Song, Yerim Choi +4
Training large language models (LLMs) is known to be challenging because of the huge computational and memory capacity requirements. To address these issues, it is common to use a…
cs.DC2024
PID-Comm: A Fast and Flexible Collective Communication Framework for Commodity Processing-in-DIMM Devices
Si Ung Noh, Junguk Hong, Chaemin Lim +5
Recent dual in-line memory modules (DIMMs) are starting to support processing-in-memory (PIM) by associating their memory banks with processing elements (PEs), allowing application…
cs.DC2024
AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping
Seongyeon Park, Junguk Hong, Jaeyong Song +3
With the advance in genome sequencing technology, the lengths of deoxyribonucleic acid (DNA) sequencing results are rapidly increasing at lower prices than ever. However, the longe…