Quasi-Static Scheduling for SCORE
Masters of Science Report
University of California, Berkeley
Dec. 7, 2004
introduced a dynamic compute model aimed at eliminating existing
barriers to the widespread efficient exploitation of reconfigurable
devices. Among other achievements this model decoupled application
design-time decisions from the run-time physical resource bindings.
The compute model uses graphs of compute pages and memory blocks
connected by stream links to capture the definition of a computation
abstracted from the detailed hardware size. An automatic run-time
scheduler is a required component in this compute model in that it
selects the temporal sequencing of virtual resources onto the physical
device, allocates hardware resources, and configures the device.
Although such a scheduler could be computationally expensive, this
work describes a quasi-static scheduling strategy that dramatically
reduces run-time overhead without restricting the full semantic power
of the dynamic dataflow graphs. This work describes the quasi-static
scheduling system, analyzes the trade-offs involved in selecting a
scheduler implementation, and highlights critical algorithms.
It pays particular attention to the temporal partitioning of compute
graphs and the management of live computation state.
Last updated: 1/19/05