Uploaded August 2022 | Updated September 2026, 5 hours ago
Caching is a classic optimization technique ubiquitous both within single hosts as well as in large distributed systems like CDNs, storage systems, databases, and data center networks. Classic solutions usually involve the omnipresent Least-Recently-Used (LRU) mechanism and its derivatives. These solutions are usually workload oblivious, and changing their configuration requires expert analysis of the system and the workload.
Recent advanced caching approaches that go well beyond LRU, which are gaining popularity, are self-adjusting and exhibit improved performance in various scenarios. We are harnessing some of the underlying design concepts to present novel caching frameworks that we are currently working on. These frameworks take into account request heterogeneity, and perform proactive caching decisions (a.k.a. speculative prefetching). We will be highlighting the design of algorithms and policies that are both dynamic and self-adjusting and consider their benefits in prominent storage system use cases.
Visit the Advanced Proactive Caching for Heterogeneous Storage Systems project page[1] for more information on the project.
Speakers
Dr. Gabriel Scalosub, Ben Gurion University of the Negev, Israel
Dr. Gil Einziger, Ben Gurion University of the Negev, Israel
Conversation Leader
Ilya Kolchinsky, Research Supervisor, Red Hat
[1] research.redhat.com/blog/research_project/advanced-proactive-caching-for-heterogeneous-storage-systems
Caching is a classic optimization technique ubiquitous both within single hosts as well as in large distributed systems like CDNs, storage systems, databases, and data center networks. Classic solutions usually involve the omnipresent Least-Recently-Used (LRU) mechanism and its derivatives. These solutions are usually workload oblivious, and changing their configuration requires expert analysis of the system and the workload.
Recent advanced caching approaches that go well beyond LRU, which are gaining popularity, are self-adjusting and exhibit improved performance in various scenarios. We are harnessing some of the underlying design concepts to present novel caching frameworks that we are currently working on. These frameworks take into account request heterogeneity, and perform proactive caching decisions (a.k.a. speculative prefetching). We will be highlighting the design of algorithms and policies that are both dynamic and self-adjusting and consider their benefits in prominent storage system use cases.
Visit the Advanced Proactive Caching for Heterogeneous Storage Systems project page[1] for more information on the project.
Speakers
Dr. Gabriel Scalosub, Ben Gurion University of the Negev, Israel
Dr. Gil Einziger, Ben Gurion University of the Negev, Israel
Conversation Leader
Ilya Kolchinsky, Research Supervisor, Red Hat
[1] research.redhat.com/blog/research_project/advanced-proactive-caching-for-heterogeneous-storage-systems
