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State-of-the-art \emph{software transactional memory (STM)} implementations achieve good performance by carefully avoiding the overhead of \emph{incremental validation} (i.e., re-reading previously read data items to avoid inconsistency)…
The hybrid runtime (HRT) model offers a path towards high performance and efficiency. By integrating the OS kernel, runtime, and application, an HRT allows the runtime developer to leverage the full feature set of the hardware and…
With the imminent slowing down of DRAM scaling, Phase Change Memory (PCM) is emerging as a lead alternative for main memory technology. While PCM achieves low energy due to various technology-specific advantages, PCM is significantly slower…
Hardware specialization is becoming a key enabler of energyefficient performance. Future systems will be increasingly heterogeneous, integrating multiple specialized and programmable accelerators, each with different memory demands.…
Virtualization technology allows currently any application run any application complex and expensive computational (the scientific applications are a good example) on heterogeneous distributed systems, which make regular use of Grid and…
Traditional machine learning depends on high-precision arithmetic and near-ideal hardware assumptions, which is increasingly challenged by variability in aggressively scaled semiconductor devices. Compute-in-memory (CIM) architectures…
Modern video-text retrieval (VTR) models excel on in-distribution benchmarks but are highly vulnerable to real-world query shifts, where the distribution of query data deviates from the training domain, leading to a sharp performance drop.…
Virtualization has become widespread across all computing environments, from edge devices to cloud systems. Its main advantages are resource management through abstraction and improved isolation of platform resources and processes. However,…
In this paper, we propose a methodology for partitioning and mapping computational intensive applications in reconfigurable hardware blocks of different granularity. A generic hybrid reconfigurable architecture is considered so as the…
Heterogeneous computing is the strategy of deploying multiple types of processing elements within a single workflow, and allowing each to perform the tasks to which is best suited. To fully harness the power of heterogeneity, we want to be…
Non-uniform performance and power consumption across the processing elements (PEs) of heterogeneous SoCs increase the computation complexity of the task scheduling problem compared to homogeneous architectures. Latency of a software-based…
The monolithic nature of widely used commodity operating systems means that vulnerabilities in one software component potentially compromise the entire kernel. Formally verifying these systems, or redesigning them altogether as…
Address translation is a major performance bottleneck in modern computing systems. Speculative address translation can hide this latency by predicting the physical address (PA) of requested data early in the pipeline. However, predicting…
Overheads in Operating System kernel network stacks and sockets have been hindering OSes from managing networking operations efficiently for years. Moreover, when building Remote Procedure Calls over TCP, certain TCP features do not match…
Recent development in lightweight OS-level virtualization, containers, provides a potential solution for running HPC applications on the cloud platform. In this work, we focus on the impact of different layers in a containerized environment…
Vision Transformers (ViTs) have recently garnered considerable attention, emerging as a promising alternative to convolutional neural networks (CNNs) in several vision-related applications. However, their large model sizes and high…
In modern computing systems, compilation employs numerous optimization techniques to enhance code performance. Source-to-source code transformations, which include control flow and datapath transformations, have been widely used in…
Virtualization technologies have evolved along with the development of computational environments since virtualization offered needed features at that time such as isolation, accountability, resource allocation, resource fair sharing and so…
This work explores the feasibility of specialized hardware implementing the Cortical Learning Algorithm (CLA) in order to fully exploit its inherent advantages. This algorithm, which is inspired in the current understanding of the mammalian…
Virtualization has gained astonishing popularity in recent decades. It is applied in several application domains, including mainframes, personal computers, data centers, and embedded systems. While the benefits of virtualization are no…