Understanding and Combating Memory Bloat in Managed Data-Intensive Systems
Abstract
The past decade has witnessed increasing demands on data-driven business intelligence that led to the proliferation of data-intensive applications. A managed object-oriented programming language such as Java is often the developer’s choice for implementing such applications, due to its quick development cycle and rich suite of libraries and frameworks. While the use of such languages makes programming easier, their automated memory management comes at a cost. When the managed runtime meets large volumes of input data, memory bloat is significantly magnified and becomes a scalability-prohibiting bottleneck.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 31, 2017
- Source ID
- 10.1145/3162626
Entities
People
- Guoqing Xu
- Kai Wang
- Khanh Nguyen
- Lu Fang
- Yingyi Bu
Organizations
- National Science Foundation
- Office of Naval Research
- University of California