A Scalable Concurrent malloc(3) Implementation for FreeBSD
By Jason Evans April. 2006
299 citations recorded by the source corpus.
Subfields: ML Systems & Hardware
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In ML Systems & Hardware
- Ali Ayub
- Alan R. Wagner
- Yoshua Bengio
- De-chuan Zhan
- Da-Wei Zhou
- Hinrich Schütze
- Timo Schick
- Allan Hanbury
Citations in the corpus
- PyTorch: An Imperative Style, High-Performance Deep Learning Library (2019, methodology): “PyTorch can rely on optimized libraries [39, 40, 41] to handle this task on CPU.”
- GraphPIM: Enabling Instruction-Level PIM Offloading in Graph Computing Frameworks (2017, methodology): “This is achieved by calling a customized pmr malloc function (similar to jemalloc [25] and tcmalloc [26]).”
- The RAMCloud Storage System (2015, methodology): “RAMCloud is 25% slower than Redis for workload A when RAMCloud runs at 90% utilization, but Redis uses the jemalloc [Evans 2006] memory allocator, whose fragmentation issues would likely require memory utilization less than 50% (see Figure 7).”
- In-Memory Big Data Management and Processing: A Survey (2015, background): “is partially alleviated by adopting the jemalloc [260] memory”
- Scalable metagenomic taxonomy classification using a reference genome database (2013, methodology): “The best candidate is found using the taxonomic lineage from the highest scoring taxonomy label.”