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Floating Point Calculation of the Cube Function on FPGAs
(Institute of Electrical and Electronics Engineers, 2023)
[Abstract]: Specialized arithmetic units allow fast and efficient computation of lesser used mathematical functions. The overall impact of those units would be negligible in a general purpose processor, as added circuitry ...
Comparison of Hardwired and Microprogrammed Statechart Implementations
(MDPI, 2020)
[Abstract]: In scientific facilities such as particle accelerators, fast and jitter-free synchronization is required in order to trigger a large number of actuators at the right time in a variety of situations. The behaviour ...
VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores
(Association for Computing Machinery, 2023-11)
[Abstract]: The increasing success and scaling of Deep Learning models demands higher computational efficiency and power. Sparsification can lead to both smaller models as well as higher compute efficiency, and accelerated ...
ParRADMeth: Identification of Differentially Methylated Regions on Multicore Clusters
(IEEE, 2023)
[Abstract]: The discovery of Differentially Methylated (DM) regions is an important research field in biology, as it can help to anticipate the risk of suffering from specific diseases. Nevertheless, the high computational ...
Enabling Hardware Affinity in JVM-Based Applications: A Case Study for Big Data
(Springer, 2020)
[Abstract]: Java has been the backbone of Big Data processing for more than a decade due to its interesting features such as object orientation, cross-platform portability and good programming productivity. In fact, most ...
Accelerating the quality control of genetic sequences through stream processing
(Association for Computing Machinery, 2023)
[Abstract]: Quality control of DNA sequences is an important data preprocessing step in many genomic analyses. However, all existing parallel tools for this purpose are based on a batch processing model, needing to have ...
SeQual-Stream: approaching stream processing to quality control of NGS datasets
(BMC, 2023-10)
[Abstract]: Background
Quality control of DNA sequences is an important data preprocessing step in many genomic analyses. However, all existing parallel tools for this purpose are based on a batch processing model, ...
Non-IID data and Continual Learning processes in Federated Learning: A long road ahead
(Elsevier, 2022)
[Abstract] Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. This decentralized approach is prone ...
A Parallel Skeleton for Divide-and-conquer Unbalanced and Deep Problems
(Springer Nature, 2021)
[Abstract] The Divide-and-conquer (D&C) pattern appears in a large number of problems and is highly suitable to exploit parallelism. This has led to much research on its easy and efficient application both in shared and ...
A Highly Optimized Skeleton for Unbalanced and Deep Divide-And-Conquer Algorithms on Multi-Core Clusters
(Springer, 2022)
[Abstract] Efficiently implementing the divide-and-conquer pattern of parallelism in distributed memory systems is very relevant, given its ubiquity, and difficult, given its recursive nature and the need to exchange tasks ...