Quantifying the performance of garbage collection vs. explicit memory management

By M. Hertz, Emery D. Berger. 2005

143 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, 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 Artificial Intelligence

1. B. Zorn
2. Emery D. Berger

In Computer Networks and Communications

1. B. Zorn
2. Emery D. Berger

In Hardware and Architecture

1. B. Zorn
2. Emery D. Berger

In ML Systems & Hardware

1. Juan Altmayer Pizzorno
2. Sam Stern
3. Emery D. Berger

Citations in the corpus

• DieHard: probabilistic memory safety for unsafe languages (2006, background): “Approaches like conservative garbage collection can impose an additional space overhead of 3X5X overmalloc /free [20, 41].”
• Triangulating Python Performance Issues with Scalene (2022, background): “Python is also a garbage collected language; because garbage collection delays memory reclamation, it can further increase the amount of memory consumed compared to native code [14].”