Serverless computing is becoming increasingly popular, enabling users to quickly launch
thousands of shortlived tasks in the cloud with high elasticity and fine-grain billing. These …

Serverless computing frameworks allow users to launch thousands of concurrent tasks with
high elasticity and fine-grain resource billing without explicitly managing computing …

Serverless computing is poised to fulfill the long-held promise of transparent elasticity and
millisecond-level pricing. To achieve this goal, service providers impose a finegrained …

Internet-scale web applications are becoming increasingly storage-intensive and rely
heavily on in-memory object caching to attain required I/O performance. We argue that the …

Serverless computing has gained attention due to its fine-grained provisioning, large-scale
multi-tenancy, and on-demand scaling. However, it also forces applications to externalize …

Serverless computing is an excellent fit for big data processing because it can scale quickly
and cheaply to thousands of parallel functions. Existing serverless platforms isolate …

Stateful serverless analytics can be enabled using a remote memory system for inter-task
communication, and for storing and exchanging intermediate data. However, existing …

The growing volume of data produced continuously in the Cloud and at the Edge poses
significant challenges for large-scale AI applications to extract and learn useful information …

In this paper, we propose ScaleStore, a novel distributed storage engine that exploits DRAM
caching, NVMe storage, and RDMA networking to achieve high performance, cost-efficiency …

The performance characteristics of modern non-volatile storage devices have led to storage
becoming a shared, rack-scale resource. System designers have an imperative to rethink …