activity
20152021
most citedCHAOS: A Parallelization Scheme for Training Convolutional Neural Networks on Intel Xeon Phi

25 citations · 27 across the 5 of their papers we have counts for

collaborators
Showing cs.DCShow all

6 papers · 1 filter

cs.DC2026

ParaWeb: Parallel Programming Patterns for Web Development

Suejb Memeti

Modern web applications increasingly require computationally intensive processing, yet JavaScript, the dominant language of the web, has traditionally been limited to a single-thre…

cs.DC2023

Enabling Dynamic Selection of Implementation Variants in Component-Based Parallel Programming for Heterogeneous Systems

Suejb Memeti

Heterogeneous systems, consisting of CPUs and GPUs, offer the capability to address the demands of compute- and data-intensive applications. However, programming such systems is ch…

cs.DC2019

Performance Modelling of Deep Learning on Intel Many Integrated Core Architectures

Andre Viebke, Sabri Pllana, Suejb Memeti +1

Many complex problems, such as natural language processing or visual object detection, are solved using deep learning. However, efficient training of complex deep convolutional neu…

cs.DC201725 cited

CHAOS: A Parallelization Scheme for Training Convolutional Neural Networks on Intel Xeon Phi

Andre Viebke, Suejb Memeti, Sabri Pllana +1

Deep learning is an important component of big-data analytic tools and intelligent applications, such as, self-driving cars, computer vision, speech recognition, or precision medic…

cs.DC2016

Combinatorial Optimization of Work Distribution on Heterogeneous Systems

Suejb Memeti, Sabri Pllana

We describe an approach that uses combinatorial optimization and machine learning to share the work between the host and device of heterogeneous computing systems such that the ove…

cs.DC20152 cited

Accelerating DNA Sequence Analysis using Intel Xeon Phi

Suejb Memeti, Sabri Pllana

Genetic information is increasing exponentially, doubling every 18 months. Analyzing this information within a reasonable amount of time requires parallel computing resources. Whil…