| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0382326 |
| utime |
20240111140821.4 |
| mtime |
20121031235959.9 |
| SCOPUS |
84906533669 |
| DOI |
10.3233/978-1-61499-041-3-579 |
| title
(primary) (eng) |
A Framework for Self-adaptive Collaborative Computing on Reconfigurable Platforms |
| specification |
| page_count |
8 s. |
| media_type |
C |
|
| serial |
| ARLID |
cav_un_epca*0382325 |
| ISBN |
978-1-61499-040-6 |
| title
|
Advances in Parallel Computing |
| page_num |
579-586 |
| publisher |
| place |
Amsterdam |
| name |
IOS Press BV |
| year |
2012 |
|
|
| keyword |
distributed systems |
| keyword |
collaborative computing |
| keyword |
resource management |
| keyword |
heterogeneous systems |
| keyword |
adaptive systems |
| keyword |
SVP |
| keyword |
MicroBlaze |
| keyword |
FPGA |
| author
(primary) |
| ARLID |
cav_un_auth*0284791 |
| name1 |
Van Tol |
| name2 |
M. W. |
| country |
NL |
|
| author
|
| ARLID |
cav_un_auth*0101179 |
| name1 |
Pohl |
| name2 |
Zdeněk |
| full_dept (cz) |
Zpracování signálů |
| full_dept |
Department of Signal Processing |
| department (cz) |
ZS |
| department |
ZS |
| institution |
UTIA-B |
| full_dept |
Department of Signal Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101213 |
| name1 |
Tichý |
| name2 |
Milan |
| full_dept (cz) |
Zpracování signálů |
| full_dept |
Department of Signal Processing |
| department (cz) |
ZS |
| department |
ZS |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
027611 |
| agency |
EC |
| country |
XE |
| agency |
EC |
| ARLID |
cav_un_auth*0225974 |
|
| abstract
(eng) |
As the number and complexity of computing devices in the environment around us increases, it is interesting to see how we could exploit that and glue them together to create larger co-operative distributed systems. This paper describes a framework for dynamically aggregating and configuring processing resources in order to meet local requirements and constraints. The capability of this framework is demonstrated by a case study using an adaptive least mean squares filter (ALMS) application. ALMS improves convergence of least mean squares filters at the cost of more resources, and allows us to demonstrate abilities of the framework such as task offloading and run-time adaptation to available resources. |
| action |
| ARLID |
cav_un_auth*0284731 |
| name |
International Conference on Parallel Computing |
| place |
Ghent |
| dates |
30.08.2011-02.09.2011 |
| country |
BE |
|
| reportyear |
2013 |
| RIV |
IN |
| num_of_auth |
3 |
| mrcbC52 |
4 A 4a 20231122135250.0 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0212577 |
| arlyear |
2012 |
| mrcbTft |
\nSoubory v repozitáři: pohl-0382326.pdf |
| mrcbU14 |
84906533669 SCOPUS |
| mrcbU56 |
278 217 |
| mrcbU63 |
cav_un_epca*0382325 Advances in Parallel Computing 978-1-61499-040-6 579 586 Amsterdam IOS Press BV 2012 |
|