ISMM 2019
11 papers
- A lock-free coalescing-capable mechanism for memory management
- Automatic GPU memory management for large neural models in TensorFlow
- Concurrent marking of shape-changing objects
- Design and analysis of field-logging write barriers
- Exploration of memory hybridization for RDD caching in Spark
- Gradual write-barrier insertion into a Ruby interpreter
- Learning when to garbage collect with random forests
- Massively parallel GPU memory compaction
- Scaling up parallel GC work-stealing in many-core environments
- Timescale functions for parallel memory allocation
- snmalloc: a message passing allocator