nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
Analyzing the impact of the MPI allreduce in distributed training of convolutional neural networks
|
Castelló, Adrián |
|
|
105 |
5 |
p. 1101-1119 |
artikel |
2 |
A symbiosis between population based incremental learning and LP-relaxation based parallel genetic algorithm for solving integer linear programming models
|
Fallah, Mohammad K |
|
|
105 |
5 |
p. 1121-1139 |
artikel |
3 |
Correction to: Parallel and distributed Processing: advances on architectures and applications of parallel systems
|
Llanos, Diego R. |
|
|
105 |
5 |
p. 913 |
artikel |
4 |
FedFlow: a federated platform to build secure sharing and synchronization services for health dataflows
|
Carrizales-Espinoza, Diana |
|
|
105 |
5 |
p. 1019-1037 |
artikel |
5 |
Multicore based least confidence query sampling strategy to speed up active learning approach for named entity recognition
|
Agrawal, Ankit |
|
|
105 |
5 |
p. 979-997 |
artikel |
6 |
Online and transparent self-adaptation of stream parallel patterns
|
Vogel, Adriano |
|
|
105 |
5 |
p. 1039-1057 |
artikel |
7 |
On the performance limits of thread placement for array databases in non-uniform memory architectures
|
Dominico, Simone |
|
|
105 |
5 |
p. 1059-1075 |
artikel |
8 |
Parallel and distributed Processing: advances on architectures and applications of parallel systems
|
Llanos, Diego R. |
|
|
105 |
5 |
p. 911 |
artikel |
9 |
Predicting number of threads using balanced datasets for openMP regions
|
Alcaraz, Jordi |
|
|
105 |
5 |
p. 999-1017 |
artikel |
10 |
Predicting physical computer systems performance and power from simulation systems using machine learning model
|
Mankodi, Amit |
|
|
105 |
5 |
p. 935-953 |
artikel |
11 |
Quantifiability: a concurrent correctness condition modeled in vector space
|
Cook, Victor |
|
|
105 |
5 |
p. 955-978 |
artikel |
12 |
SPBench: a framework for creating benchmarks of stream processing applications
|
Garcia, Adriano Marques |
|
|
105 |
5 |
p. 1077-1099 |
artikel |
13 |
Using machine learning to model the training scalability of convolutional neural networks on clusters of GPUs
|
Barrachina, Sergio |
|
|
105 |
5 |
p. 915-934 |
artikel |