As high-level synthesis techniques gain acceptance among designers, it is important to be able to provide a robust system which can handle large designs in short execution times, producing high-quality results. Scheduling is one of the most complex tasks in high-level synthesis, and although many algorithms exist for solving the scheduling problem, it remains a main source of inefficiency by either not producing high-quality results, not taking into account realistic design requirements, or requiring unacceptable execution times. One of the main problems in scheduling is the dichotomy between control and data. Many algorithms to date have been able to provide scheduling solutions by looking only at either the data part or the control part of the design. This has been done in order to simplify the problem; however, it has resulted in many algorithms unable to handle efficiently large designs with complex control and data functionality. This paper presents algorithms for combining dataflow and control-flow techniques into a robust scheduling system. The main characteristics of this system are as follows: 1) it uses path-based techniques for efficient handling of control and mutual exclusiveness (for resource sharing), 2) it allows operation reordering and parallelism extraction within the context of pathbased scheduling, 3) it contains a control partitioning algorithm for design space exploration as well as for reducing the number of control paths, and 4) it combines the above algorithms into an adaptive scheduling system which is capable of trading optimality for execution time on-the-fly. Results involving billions of paths are presented and analyzed.

Leading-edge systems-on-chip (SoC) being designed today could reach 20 Million gates and 0.5 to 1 GHz operating frequency. In order to implement such systems, designers are increasingly relying on reuse of intellectual property (IP) blocks. Since IP blocks are pre-designed and pre-verified, the designer can concentrate on the complete system without having to worry about the correctness or performance of the individual components. That is the goal, in theory. In practice, assembling an SoC using IP blocks is still an error-prone, labor-intensive and time-consuming process. This paper discusses the main challenges in SoC designs using IP blocks and elaborates on the methodology and tools being put in place at IBM for addressing the problem. It explains IBM's SoC architecture and gives algorithmic details on the high-level tools being developed for SoC design.

Power dissipation has become a critical design metric in microprocessor-based system design. In a multi-core system, running multiple applications, power and performance can be dynamically traded off using an integrated power management (PM) unit. This PM unit monitors the performance and power of each core and dynamically adjusts the individual voltages and frequencies in order to maximize system performance under a given power budget (usually set by the operating system). This paper presents a performance and power analysis methodology, featuring a simulation model for multi-core systems that can be easily reconfigured for different scenarios and a PM infrastructure for the exploration and analysis of PM algorithms. Two algorithms have been implemented: one for discrete and one for continuous power modes based on non-linear programming. Extensive experiments are reported, illustrating the effect of power management both at the core and the chip level.

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