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There is a great diversity of clustering and community detection algorithms, which are key components of many data analysis and exploration systems. To the best of our knowledge, however, there does not exist yet any uniform benchmarking…
The trend towards highly parallel multi-processing is ubiquitous in all modern computer architectures, ranging from handheld devices to large-scale HPC systems; yet many applications are struggling to fully utilise the multiple levels of…
Cloud workloads combine software components from different parties to process sensitive data. Each component has its own trust model - it must protect its assets from the rest of the system, yet share sensitive data with components it…
We present a user-friendly and versatile tool for laser frequency stabilization. Its main focus is spectroscopy locking, but the software is suitable for lock-in techniques in general as well as bare PID operation. Besides allowing for…
This thesis develops signal-processing algorithms and implementation schemes under constraints of minimal parallelism and memory space, with the goal of improving energy efficiency of low-power computing hardware. We propose (i) a…
By providing highly efficient one-sided communication with globally shared memory space, Partitioned Global Address Space (PGAS) has become one of the most promising parallel computing models in high-performance computing (HPC). Meanwhile,…
This paper introduces an effort to incorporate reconfigurable logic (FPGA) components into a software programming model. For this purpose, we have implemented a hardware engine for remote memory communication between hardware computation…
To address increasing compute demand from recent multi-model workloads with heavy models like large language models, we propose to deploy heterogeneous chiplet-based multi-chip module (MCM)-based accelerators. We develop an advanced…
The ability of the foundation models heavily relies on large-scale, diverse, and high-quality pretraining data. In order to improve data quality, researchers and practitioners often have to manually curate datasets from difference sources…
Machine Learning (ML) models execute several parallel computations including Generalized Matrix Multiplication, Convolution, Dropout, etc. These computations are commonly executed on Graphics Processing Units (GPUs), by dividing the…
Pipeline parallelism is an essential distributed parallelism method. Increasingly complex and diverse DNN models necessitate meticulously customized pipeline schedules for performance. However, existing practices typically rely on…
Passive and linear nonreciprocal networks at microwave frequencies hold great promises in enabling new front-end architectures for wireless communication systems. Their nonreciprocity has been achieved by disrupting the time-reversal…
FPGA-based hardware accelerators have received increasing attention mainly due to their ability to accelerate deep pipelined applications, thus resulting in higher computational performance and energy efficiency. Nevertheless, the amount of…
As multimodal and AI-driven services exchange hundreds of megabytes per request, existing IPC runtimes spend a growing share of CPU cycles on memory copies. Although both hardware and software mechanisms are exploring memory offloading,…
Embedded systems are parts of our daily life and used in many fields. They can be found in smartphones or in modern cars including GPS, light/rain sensors and other electronic assistance mechanisms. These systems may handle sensitive data…
Rust is a popular memory-safe systems programming language. In order to interact with hardware or call into non-Rust libraries, Rust provides \emph{unsafe} language features that shift responsibility for ensuring memory safety to the…
This paper aims at contributing to the ongoing debate on how to bring programmability of stateful packet processing tasks inside the network switches, while retaining platform independency. Our proposed approach, named "Open Packet…
Confidential computing safeguards sensitive computations from untrusted clouds, with Confidential Virtual Machines (CVMs) providing a secure environment for guest OS. However, CVMs often come with large and vulnerable operating system…
The 6TiSCH protocol stack plays a vital role in enabling reliable and energy-efficient communications for the Industrial Internet of Things (IIoT). However, it faces challenges, including prolonged network formation, inefficient parent…
Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer, but…