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Probing the Efficacy of Hardware-Aware Weight Pruning to Optimize the SpMM routine on Ampere GPUs
(Institute of Electrical and Electronics Engineers, 2022)
[Abstract]: The Deep Learning (DL) community found in pruning techniques a good way to reduce the models' resource and energy consumption. These techniques lead to smaller sparse models, but sparse computations in GPUs ...
Efficient high-precision integer multiplication on the GPU
(SAGE Journals, 2022-03)
[Abstract]: The multiplication of large integers, which has many applications in computer science, is an operation that can be expressed as a polynomial multiplication followed by a carry normalization. This work develops ...
Walking Recognition in Mobile Devices
(MDPI AG, 2020-02-21)
[Abstract] Presently, smartphones are used more and more for purposes that have nothing to do with phone calls or simple data transfers. One example is the recognition of human activity, which is relevant information for ...
SeQual: Big Data Tool to Perform Quality Control and Data Preprocessing of Large NGS Datasets
(Institute of Electrical and Electronics Engineers, 2020-08-07)
[Abstract]
This paper presents SeQual, a scalable tool to efficiently perform quality control of large genomic datasets. Our tool currently supports more than 30 different operations (e.g., filtering, trimming, formatting) ...
Exploratory Data Analysis and Data Envelopment Analysis of Construction and Demolition Waste Management in the European Economic Area
(M D P I AG, 2020-06-18)
[Abstract]
This paper deals with the efficiency and sustainability of Construction and Demolition Waste (CDW) management in 30 Member States of the European Economic Area (EEA) (the 28 European Union countries plus Norway ...
Parallel ant colony optimization for the training of cell signaling networks
(Elsevier, 2022)
[Abstract]: Acquiring a functional comprehension of the deregulation of cell signaling networks in disease allows progress in the development of new therapies and drugs. Computational models are becoming increasingly popular ...
The New UPC++ DepSpawn High Performance Library for Data-Flow Computing with Hybrid Parallelism
(Springer, 2022)
[Abstract] Data-flow computing is a natural and convenient paradigm for expressing parallelism. This is particularly true for tools that automatically extract the data dependencies among the tasks while allowing to exploit ...
Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition
(Elsevier, 2022)
[Abstract] Deep Learning approaches have brought solutions, with impressive performance, to general classification problems where wealthy of annotated data are provided for training. In contrast, less progress has been ...
SparkEC: speeding up alignment-based DNA error correction tools
(BioMed Central (Springer), 2022)
[Abstract]: In recent years, huge improvements have been made in the context of sequencing genomic data under what is called Next Generation Sequencing (NGS). However, the DNA reads generated by current NGS platforms are ...
A Software Cache Autotuning Strategy for Dataflow Computing with UPC++ DepSpawn
(Wiley, 2021)
[Abstract] Dataflow computing allows to start computations as soon as all their dependencies are satisfied. This is particularly useful in applications with irregular or complex patterns of dependencies which would otherwise ...