Micro-architectural Analysis of In-memory OLTP

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Long plasma duration operation analyses with an international multi-machine (tokamaks and stellarators) database

Stefano Coda, Jeffrey Huang

Combined high-fusion performance and long-pulse operation is one of the key integration challenges for fusion energy development in magnetic devices. Addressing these challenges requires an integrated vision of physics and engineering aspects with the purp ...

IOP Publishing Ltd2024

Oligolithic Cross-task Optimizations across Isolated Workloads

Anastasia Ailamaki, Eleni Zapridou, Panagiotis Sioulas

Enterprises collect data in large volumes and leverage them to drive numerous concurrent decisions and business processes. Their teams deploy multiple applications that often operate concurrently on the same data and infrastructure but have widely differen ...

2024

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Alireza Karimi, Mert Eyuboglu, Nathan Russell Powell

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Panagiotis Sioulas

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

EPFL2023

Determining an optimum quantity of interleaved instruction streams of defined coroutines

Anastasia Ailamaki, Georgios Psaropoulos

A method for optimizing memory access for database operations is provided. The method may include performing a first database operation by at least executing a first instruction stream associated with the first database operation. The first database opera ...

2023

HPCache: memory-efficient OLAP through proportional caching revisited

Anastasia Ailamaki, Hamish Mcniece Hill Nicholson, Periklis Chrysogelos

Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- and time-based caching decisions, however, are a proxy of the expected query ...

Springer2023

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Felix Schürmann, Pramod Shivaji Kumbhar, Omar Awile, Snehal Pramod Kumbhar, Ioannis Magkanaris

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

ACM2023

TiC-SAT: Tightly-coupled Systolic Accelerator for Transformers

David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi, Joshua Alexander Harrison Klein

Transformer models have achieved impressive results in various AI scenarios, ranging from vision to natural language processing. However, their computational complexity and their vast number of parameters hinder their implementations on resource-constraine ...

2023

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