157 citations · 240 across the 16 of their papers we have counts for
17 papers
Memory Wall is not gone: A Critical Outlook on Memory Architecture in Digital Neuromorphic Computing
Amirreza Yousefzadeh, Sameed Sohail, Ana Lucia Varbanescu
The rapid advancement of neuromorphic technology aims to address the memory wall challenge inherent in conventional von Neumann architectures. This paper critically examines curren…
Graph2TS: Structure-Controlled Time Series Generation via Quantile-Graph VAEs
Shaoshuai Du, Joze M. Rozanec, Andy Pimentel +1
Although recent generative models can produce time series with close marginal distributions, they often face a fundamental tension between preserving global temporal structure and…
Tide: A Customisable Dataset Generator for Anti-Money Laundering Research
Montijn van den Beukel, Jože Martin Rožanec, Ana-Lucia Varbanescu
The lack of accessible transactional data significantly hinders machine learning research for Anti-Money Laundering (AML). Privacy and legal concerns prevent the sharing of real fi…
Reducing Compute Waste in LLMs through Kernel-Level DVFS
Jeffrey Spaan, Kuan-Hsun Chen, Ana-Lucia Varbanescu
The rapid growth of AI has fueled the expansion of accelerator- or GPU-based data centers. However, the rising operational energy consumption has emerged as a critical bottleneck a…
InTreeger: An End-to-End Framework for Integer-Only Decision Tree Inference
Duncan Bart, Bruno Endres Forlin, Ana-Lucia Varbanescu +2
Integer quantization has emerged as a critical technique to facilitate deployment on resource-constrained devices. Although they do reduce the complexity of the learning models, th…
FPGA Innovation Research in the Netherlands: Present Landscape and Future Outlook
Nikolaos Alachiotis, Sjoerd van den Belt, Steven van der Vlugt +10
FPGAs have transformed digital design by enabling versatile and customizable solutions that balance performance and power efficiency, yielding them essential for today's diverse co…
Novel Approaches for ML-Assisted Particle Track Reconstruction and Hit Clustering
Uraz Odyurt, Nadezhda Dobreva, Zef Wolffs +6
Track reconstruction is a vital aspect of High-Energy Physics (HEP) and plays a critical role in major experiments. In this study, we delve into unexplored avenues for particle tra…
Model Parallelism on Distributed Infrastructure: A Literature Review from Theory to LLM Case-Studies
Felix Brakel, Uraz Odyurt, Ana-Lucia Varbanescu
Neural networks have become a cornerstone of machine learning. As the trend for these to get more and more complex continues, so does the underlying hardware and software infrastru…
Lessons Learned Migrating CUDA to SYCL: A HEP Case Study with ROOT RDataFrame
Jolly Chen, Monica Dessole, Ana Lucia Varbanescu
The world's largest particle accelerator, located at CERN, produces petabytes of data that need to be analysed efficiently, to study the fundamental structures of our universe. ROO…
Using Evolutionary Algorithms to Find Cache-Friendly Generalized Morton Layouts for Arrays
Stephen Nicholas Swatman, Ana-Lucia Varbanescu, Andy D. Pimentel +2
The layout of multi-dimensional data can have a significant impact on the efficacy of hardware caches and, by extension, the performance of applications. Common multi-dimensional l…
Reduced Simulations for High-Energy Physics, a Middle Ground for Data-Driven Physics Research
Uraz Odyurt, Stephen Nicholas Swatman, Ana-Lucia Varbanescu +1
Subatomic particle track reconstruction (tracking) is a vital task in High-Energy Physics experiments. Tracking is exceptionally computationally challenging and fielded solutions,…
Future Computer Systems and Networking Research in the Netherlands: A Manifesto
Alexandru Iosup, Fernando Kuipers, Ana Lucia Varbanescu +6
Our modern society and competitive economy depend on a strong digital foundation and, in turn, on sustained research and innovation in computer systems and networks (CompSys). With…
The Future is Big Graphs! A Community View on Graph Processing Systems
Sherif Sakr, Angela Bonifati, Hannes Voigt +38
Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users a…
Scalability Model for the LOFAR Direction Independent Pipeline
A. P. Mechev, T. W. Shimwell, A. Plaat +3
LOFAR is a leading aperture synthesis telescope operated in the Netherlands with stations across Europe. The LOFAR Two-meter Sky Survey (LoTSS) will produce more than 3000 14 TB da…
Using Graph Properties to Speed-up GPU-based Graph Traversal: A Model-driven Approach
Merijn Verstraaten, Ana Lucia Varbanescu, Cees de Laat
While it is well-known and acknowledged that the performance of graph algorithms is heavily dependent on the input data, there has been surprisingly little research to quantify and…
COFFEE: an Optimizing Compiler for Finite Element Local Assembly
Fabio Luporini, Ana Lucia Varbanescu, Florian Rathgeber +4
The numerical solution of partial differential equations using the finite element method is one of the key applications of high performance computing. Local assembly is its charact…
An Empirical Study of Intel Xeon Phi
Jianbin Fang, Ana Lucia Varbanescu, Henk Sips +3
With at least 50 cores, Intel Xeon Phi is a true many-core architecture. Featuring fairly powerful cores, two cache levels, and very fast interconnections, the Xeon Phi can get a t…