In this talk, we will present the newly EU-funded project AERO (Accelerated EU Cloud) whose mission is to bring up and optimize the software stack of cloud deployments on top of the EU processor. After providing an overview of the AERO project, we will expand on two main components of the software stack to enable seamless acceleration of various programming languages on RISC-V architectures; namely, ComputeAorta which enables the generation of RISC-V vector instructions from SPIR-V binary modules, and TornadoVM which enables transparent hardware acceleration of managed applications. Finally, we will describe how the ongoing integration of ComputeAorta and TornadoVM will enable a plethora of applications from managed languages to harness RISC-V auto-vectorization completely transparently to developers.

We advocate and originally design FaaSCell, an intra-node orchestrator for serverless functions. It aims to enable single-node resource management and performance studies, while remaining compatible with the distributed software stack of FaaS. FaaSCell could potentially be integrated with Kubernetes and its ecosystem, or with any other upper-layer component or platform that may be used for cluster-wide orchestration of FaaS deployments.

Scaling up the performance of managed applications on Non-Uniform Memory Access (NUMA) architectures has been a challenging task, as it requires a good understanding of the underlying architecture and managed runtime environments (MRE). Prior work has studied this problem from the scope of specific components of the managed runtimes, such as the Garbage Collectors, as a means to increase the NUMA awareness in MREs.

In this paper, we follow a different approach that complements prior work by studying the behavior of managed applications on NUMA architectures during mutation time. At first, we perform a characterization study that classifies several Dacapo and Renaissance applications as per their scalability-critical properties. Based on this study, we propose a novel lightweight mechanism in MREs for optimizing the scalability of managed applications on NUMA systems, in an application-agnostic way. Our experimental results show that the proposed mechanism can result in relative performance ranging from 0.66x up to 3.29x, with a geometric mean of 1.11x, against a NUMA-agnostic execution.

In recent years, the Java Virtual Machine has evolved from a cross-ISA virtualization layer to a system that can also offer multilingual support. GraalVM paved the way to enable the interoperability of Java with other programming languages, such as Java, Python, R and even C++, that can run on top of the Truffle framework in a unified manner. Additionally, there have been numerous academic and industrial endeavors to bridge the gap between the JVM and modern heterogeneous hardware resources. All these efforts beacon the opportunity to use the JVM as a unified system that enables interoperability between multiple programming languages and multiple heterogeneous hardware resources.
In this paper, we focus on the interoperability of code that accelerates applications on heterogeneous hardware with multiple programming languages. To realize that concept, we employ TornadoVM, a state-of-the-art software for enabling various JDK distributions to exploit hardware acceleration. Although TornadoVM can transparently generate heterogeneous code at runtime, there are several challenges that hinder the portability of the generated code to other programming languages and systems. Therefore, we analyze all challenges and propose a set of modifications at the compiler and runtime levels to constitute Java as a prototyping language for the generation of heterogeneous code that can be used by other programming languages and systems.