A Heuristic Scheduler for Port-Constrained Floating-Point Pipelines

We describe a heuristic scheduling approach for optimizing floating-point pipelines subject to input port constraints. The objective of our technique is to maximize functional unit reuse while minimizing the following performance metrics in the generated circuit: (1) maximum multiplexer fanin, (2) datapath fanout, (3) number of multiplexers, and (4) number of registers. For a set of systems biology markup language (SBML) benchmark expressions, we compare the resource usages given by our method to those given by a branch-and-bound enumeration of all valid schedules. Compared with the enumeration results, our heuristic requires on average 33.4% less multiplexer bits and 32.9% less register bits than the worse case, while only requiring 14% more multiplexer bits and 4.5% more register bits than the optimal case. We also compare our results against those given by the state-of-art high-level synthesis tool Xilinx AutoESL. For the most complex of our benchmark expressions, our synthesis technique requires 20% less FPGA slices than AutoESL

A scheduling algorithm for multiport memory minimization in datapath synthesis

Abstract- In this paper, we present a new scheduling algorithms that generates area-efficient register transfer level datapaths with multiport memories. The proposed scheduling algorithm assigns an operation to a specific control step such that maximal sharing of functional units can be achieved with minimal number of memory ports, while satisfying given constraints. We propose a measure of multiport memory cost, MAV (Multiple Access Variable) which is defined as a variable accessed at several control steps, and overall memory cost is reduced by equally distributing the MAVs throughout all the control steps. When compared with previous approaches for several benchmarks available from the literature, the proposed algorithm generates the datapaths with less memory modules and interconnection structures by reflecting the memory cost in the scheduling process

A Methodology to Design Pipelined Simulated Annealing Kernel Accelerators on Space-Borne Field-Programmable Gate Arrays

Increased levels of science objectives expected from spacecraft systems necessitate the ability to carry out fast on-board autonomous mission planning and scheduling. Heterogeneous radiation-hardened Field Programmable Gate Arrays (FPGAs) with embedded multiplier and memory modules are well suited to support the acceleration of scheduling algorithms. A methodology to design circuits specifically to accelerate Simulated Annealing Kernels (SAKs) in event scheduling algorithms is shown. The main contribution of this thesis is the low complexity scoring calculation used for the heuristic mapping algorithm used to balance resource allocation across a coarse-grained pipelined data-path. The methodology was exercised over various kernels with different cost functions and problem sizes. These test cases were benchedmarked for execution time, resource usage, power, and energy on a Xilinx Virtex 4 LX QR 200 FPGA and a BAE RAD 750 microprocessor