Name
Abstract | ||
|---|---|---|
We propose a design optimization framework for adap- tive real-time streaming applications. The main contribu- tion is a hybrid approach for performance analysis com- bining formal analysis and simulation using a two-phase framework. We formulate the scheduling problem of adap- tive streaming applications with ILP analysis, and use the simulation based on the synchronous model of computation to ensure throughput guarantees. We finally illustrate the capabilities of our methodology by experiments. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2180887.2180888 | ACM Transactions on Embedded Computing Systems (TECS) |
Keywords | Field | DocType |
optimisation,cumulative function,design optimization,reconfigurable fpga,design trade-offs,reconfigurable architectures,application execution semantics,novel compile-time analysis framework,two-phase framework,synchronous computation model,scheduling problem,varying design concern,public domain constraint solver,ilp analysis,performance analysis framework,adaptive real-time synchronous data,video streaming,field programmable gate arrays,adaptive systems,performance analysis,adaptive real-time streaming,data stream,event model,adaptive scheduling,adaptive real-time streaming applications,timing analysis,computer and information science,reconfiguration,cumulant,real time,public domain,design,model of computation,data models,computational modeling,throughput | Data modeling,Data stream mining,Job shop scheduling,Adaptive system,Computer science,Parallel computing,Constraint satisfaction problem,Real-time computing,Throughput,Synchronous Data Flow,Control reconfiguration | Journal |
Volume | Issue | ISSN |
11S | 1 | 1539-9087 |
ISBN | Citations | PageRank |
978-1-4244-2612-6 | 5 | 0.52 |
References | Authors | |
29 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Zhu | 1 | 48 | 3.76 |
| Ingo Sander | 2 | 230 | 29.54 |
| Axel Jantsch | 3 | 1875 | 169.83 |