11 citations · 37 across the 21 of their papers we have counts for
18 papers · 1 filter
STRETCH: Virtual Shared-Nothing Parallelism for Scalable and Elastic Stream Processing
Vincenzo Gulisano, Hannaneh Najdataei, Yiannis Nikolakopoulos +3
Stream processing applications extract value from raw data through Directed Acyclic Graphs of data analysis tasks. Shared-nothing (SN) parallelism is the de-facto standard to scale…
Consistent Lock-free Parallel Stochastic Gradient Descent for Fast and Stable Convergence
Karl Bäckström, Ivan Walulya, Marina Papatriantafilou +1
Stochastic gradient descent (SGD) is an essential element in Machine Learning (ML) algorithms. Asynchronous parallel shared-memory SGD (AsyncSGD), including synchronization-free al…
Performance Modeling and Vertical Autoscaling of Stream Joins
Hannaneh Najdataei, Vincenzo Gulisano, Alessandro V. Papadopoulos +3
Streaming analysis is widely used in cloud as well as edge infrastructures. In these contexts, fine-grained application performance can be based on accurate modeling of streaming o…
MindTheStep-AsyncPSGD: Adaptive Asynchronous Parallel Stochastic Gradient Descent
Karl Bäckström, Marina Papatriantafilou, Philippas Tsigas
Stochastic Gradient Descent (SGD) is very useful in optimization problems with high-dimensional non-convex target functions, and hence constitutes an important component of several…
D2.4 Report on the final prototype of programming abstractions for energy-efficient inter-process communication
Phuong Hoai Ha, Vi Ngoc-Nha Tran, Ibrahim Umar +5
Work package 2 (WP2) aims to develop libraries for energy-efficient inter-process communication and data sharing on the EXCESS platforms. The Deliverable D2.4 reports on the final…
D2.3 Power models, energy models and libraries for energy-efficient concurrent data structures and algorithms
Phuong Hoai Ha, Vi Ngoc-Nha Tran, Ibrahim Umar +5
This deliverable reports the results of the power models, energy models and libraries for energy-efficient concurrent data structures and algorithms as available by project month 3…