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This thesis delves into the critical study of particle transport in matter, particularly emphasising its implications for machine protection at CERN's accelerator complex and facilities. To conduct studies of this nature, FLUKA and Geant4 stand out within ...

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 ...

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 ...

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 ...

Most modern in-memory online transaction processing (OLTP) engines rely on multi-version concurrency control (MVCC) to provide data consistency guarantees in the presence of conflicting data accesses. MVCC improves concurrency by generating a new version o ...

Modern data management systems aim to provide both cutting-edge functionality and hardware efficiency. With the advent of AI-driven data processing and the post-Moore Law era, traditional memory-bound scale-up data management operations face scalability ch ...

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

The demise of Moore's Law and Dennard scaling has resulted in diminishing performance gains for general-purpose processors, and so has prompted a surge in academic and commercial interest for hardware accelerators. Specialized hardware has already redefine ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

Embedded systems confront two opposite goals: low-power operation and high performance. The current trend to reach these goals is toward heterogeneous platforms, including multi-core architectures with heterogeneous cores and hardware accelerators. The lat ...

Calcul intensif

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Bridging Monte Carlo worlds: a new framework for accelerator simulations applied on shielding and machine protection studies

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

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

Rebooting Virtual Memory with Midgard

One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version Storage

Post-Moore's Law Fusion: High-Bandwidth Memory, Accelerators, and Native Half-Precision Processing for CPU-Local Analytics

Chaosity: Understanding Contemporary NUMA-architectures

uKharon: A Membership Service for Microsecond Applications

Building Chips Faster: Hardware-Compiler Co-Design for Accelerated RTL Simulation

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Acceleration of Control Intensive Applications on Coarse-Grained Reconfigurable Arrays for Embedded Systems