Related papers: User-guided Page Merging for Memory Deduplication …
One key to enabling high-performance serverless computing is to mitigate cold-starts. Current solutions utilize a warm pool to keep function alive: a warm-start can be analogous to a CPU cache-hit. However, modern cache has multiple…
Serverless computing is an emerging cloud computing paradigm for developing applications at the function level, known as serverless functions. Due to the highly dynamic execution environment, multiple identical runs of the same serverless…
WebAssembly has emerged as a lightweight and portable runtime to execute serverless functions, particularly in heterogeneous and resource-constrained environments such as the Edge Cloud Continuum. However, the performance benefits versus…
Serverless computing provides infrastructure management and elastic auto-scaling, therefore reducing operational overhead. By design serverless functions are stateless, which means they typically leverage external remote services to store…
Adopting serverless computing to edge networks benefits end-users from the pay-as-you-use billing model and flexible scaling of applications. This paradigm extends the boundaries of edge computing and remarkably improves the quality of…
Operating a scalable and reliable server application, such as publish/subscribe (pub/sub) systems, requires tremendous development efforts and resources. The emerging serverless paradigm simplifies the development and deployment of highly…
The convergence of high-performance computing (HPC) and artificial intelligence (AI) is driving the emergence of increasingly complex parallel applications and workloads. These workloads often combine multiple parallel runtimes within the…
Serverless computing is an approach to cloud computing that allows programmers to run serverless functions in response to external events. Serverless functions are priced at sub-second granularity, support transparent elasticity, and…
Distributed Machine Learning refers to the practice of training a model on multiple computers or devices that can be called nodes. Additionally, serverless computing is a new paradigm for cloud computing that uses functions as a…
Serverless computing, also known as Functions-as-a-Service, is a recent paradigm aimed at simplifying the programming of cloud applications. The idea is that developers design applications in terms of functions, which are then deployed on a…
Serverless computing at the edge requires lightweight execution environments to minimize cold start latency, especially in Urgent Edge Computing (UEC). This paper compares WebAssembly and unikernel-based MicroVMs for serverless workloads.…
Graphics Processing Units (GPUs) leverage massive parallelism and large memory bandwidth to support high-performance computing applications, such as multimedia rendering, crypto-mining, deep learning, and natural language processing. These…
Serverless Computing is a virtualisation-related paradigm that promises to simplify application management and to solve the last challenges in the field: scale down and easy to use. The implied cost reduction, coupled with a simplified…
We leverage eBPF in order to implement custom policies in the Linux memory subsystem. Inspired by CBMM, we create a mechanism that provides the kernel with hints regarding the benefit of promoting a page to a specific size. We introduce a…
Processing-in-Memory (PIM) enhances memory with computational capabilities, potentially solving energy and latency issues associated with data transfer between memory and processors. However, managing concurrent computation and data flow…
Modern enterprise servers are increasingly embracing tiered memory systems with a combination of low latency DRAMs and large capacity but high latency non-volatile main memories (NVMMs) such as Intel's Optane DC PMM. Prior works have…
We present FunLess, a Function-as-a-Service (FaaS) platform tailored for the private edge cloud system. FunLess responds to recent trends that advocate for extending the coverage of serverless computing to private edge cloud systems and…
Function-as-a-Service (FaaS) has raised a growing interest in how to "tame" serverless computing to enable domain-specific use cases such as data-intensive applications and machine learning (ML), to name a few. Recently, several systems…
The traditional cloud-centric approach for Deep Learning (DL) requires training data to be collected and processed at a central server which is often challenging in privacy-sensitive domains like healthcare. Towards this, a new learning…
Serverless platforms face a trade-off: conventional cluster managers like Kubernetes offer compatibility for co-locating Function-as-a-Service (FaaS) and Backend-as-a-Service (BaaS) components of serverless applications, at the cost of high…