Loop scheduling is an important problem in parallel processing. The retiming technique reorganizes an iteration; the unfolding technique schedules several iterations together. We combine these two techniques to obtain a static schedule with a reduced average computation time per iteration. We first prove that the order of retiming and unfolding is immaterial for scheduling a data-flow graph (DFG). From this nice property, we present a polynomial-time algorithm on the original DFG, before unfolding, to find the minimum-rate static schedule for a given unfolding factor. For the case of a unit-time DFG, efficient checking and retiming algorithms are presented
We consider the resource-constrained scheduling of loops with inter-iteration dependencies. A loop i...
Many common iterative or recursive DSP applications can be represented by synchronous data-flow grap...
Synchronous dataflow graphs (SDFGs) are used extensively to model streaming applications. An SDFG ca...
Many computation-intensive or recursive applications commonly found in digital signal processing and...
Many iterative or recursive applications commonly found in DSP and image processing applications can...
Many iterative or recursive applications commonly found in DSP and image processing applications can...
Synchronous dataflow graphs (SDFGs) are widely used to represent digital signal processing algorithm...
Abstract—Synchronous dataflow graphs (SDFGs) are widely used to represent DSP algorithms and streami...
This paper presents an exact method and a heuristic method for static rate-optimal multiprocessor sc...
This paper presents an exact method and a heuristic method for static rate-optimal multiprocessor sc...
Four scheduling strategies for dataflow graphs onto parallel processors are classified: (1) fully dy...
Synchronous dataflow graphs (SDFGs) are widely used to model digital signal processing (DSP) and str...
Many common iterative or recursive DSP applications can be represented by synchronous data-flow grap...
This paper addresses the issue of determining the iteration bound for a synchronous data flow graph ...
Abstract—Synchronous dataflow graphs (SDFGs) are widely used to model digital signal processing (DSP...
We consider the resource-constrained scheduling of loops with inter-iteration dependencies. A loop i...
Many common iterative or recursive DSP applications can be represented by synchronous data-flow grap...
Synchronous dataflow graphs (SDFGs) are used extensively to model streaming applications. An SDFG ca...
Many computation-intensive or recursive applications commonly found in digital signal processing and...
Many iterative or recursive applications commonly found in DSP and image processing applications can...
Many iterative or recursive applications commonly found in DSP and image processing applications can...
Synchronous dataflow graphs (SDFGs) are widely used to represent digital signal processing algorithm...
Abstract—Synchronous dataflow graphs (SDFGs) are widely used to represent DSP algorithms and streami...
This paper presents an exact method and a heuristic method for static rate-optimal multiprocessor sc...
This paper presents an exact method and a heuristic method for static rate-optimal multiprocessor sc...
Four scheduling strategies for dataflow graphs onto parallel processors are classified: (1) fully dy...
Synchronous dataflow graphs (SDFGs) are widely used to model digital signal processing (DSP) and str...
Many common iterative or recursive DSP applications can be represented by synchronous data-flow grap...
This paper addresses the issue of determining the iteration bound for a synchronous data flow graph ...
Abstract—Synchronous dataflow graphs (SDFGs) are widely used to model digital signal processing (DSP...
We consider the resource-constrained scheduling of loops with inter-iteration dependencies. A loop i...
Many common iterative or recursive DSP applications can be represented by synchronous data-flow grap...
Synchronous dataflow graphs (SDFGs) are used extensively to model streaming applications. An SDFG ca...