Language Virtualization for Heterogeneous Parallel Computing

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In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

A virtual machine interacts with its host environment through virtual devices, driven by virtual device messages, e.g., I/O operations. By issuing crafted messages, an adversary can exploit a vulnerability in a virtual device to escape the virtual machine, ...

Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...

Fuzzing reliably and efficiently finds bugs in software, including operating system kernels. In general, higher code coverage leads to the discovery of more bugs. This is why most existing kernel fuzzers adopt strategies to generate a series of inputs that ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

In high energy physics, semiconductor-based sensors are widely used in particle tracking applications. These sensors are typically glued on low-mass cooling substrates, which guarantee the correct thermal management and, at the same time, minimise their in ...

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

We consider fundamental algorithmic number theoretic problems and their relation to a class of block structured Integer Linear Programs (ILPs) called 2-stage stochastic. A 2-stage stochastic ILP is an integer program of the form min{c(T)x vertical bar Ax = ...

During the design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated according to key performance indicators to achieve the optimal system performance. It is a highly complex process involving multidisciplinary s ...

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

This paper presents a new All-In-One (AIO) implementation of an existing formulation to design adaptive structures through Total Energy Optimization (TEO). The method implemented in previous work is a nested optimization process, here named TEO-Nested. Num ...

Language Virtualization for Heterogeneous Parallel Computing

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Approximation Algorithms for Allocation and Network Design

VIDEZZO: Dependency-aware Virtual Device Fuzzing

Design Space Exploration for Partitioning Dataflow Program on CPU-GPU Heterogeneous System

ACTOR: Action-Guided Kernel Fuzzing

Rebooting Virtual Memory with Midgard

Interlocking modular microfluidic cooling substrates for future high energy physics experiments

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

The double exponential runtime is tight for 2-stage stochastic ILPs

A semantic-driven tradespace framework to accelerate aircraft manufacturing system design

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

Minimum energy adaptive structures – All-In-One problem formulation