Transaction-level modeling is an essential component of system-level design. This paper advocates using rendezvous, a construct common to concurrent programming languages, as a theoretical foundation for transactions. Compared to regular function calls, rendezvous are atomic and support multipartiness and parallel composition. However, scheduling multiparty rendezvous is a challenging task due to its NP-hard complexity. This paper describes a heuristic algorithm that significantly reduces the scheduling complexity in practice. It first constructs a relationship graph among rendezvous. It then simplifies the graph and translates it into a decision tree, which assists the scheduler in partitioning and pruning the search space. Our experimental results show that the algorithm is able to improve the efficiency of the scheduler significantly.

Technology trends are driving parallel on-chip architectures in the form of multiprocessor systems-on-a-chip (MPSoCs) and chip multiprocessors (CMPs). In these systems, the increasing on-chip communication demand among the computation elements necessitates the use of scalable, high-bandwidth network-on-chip (NoC) fabrics instead of dedicated interconnects and shared buses. As transistor feature sizes are further miniaturized, more complicated NoC architectures become feasible that can support more demanding applications. Given the myriad emerging software-hardware combinations, for cost-effectiveness, a system designer critically needs to prune this widening NoC design-space to predict the interconnect fabric(s) that best balance(s) cost/performance, before the actual design process begins. This prompted us to develop Polaris, a system-level roadmapping toolchain for on-chip interconnection networks that helps designers predict the most suitable interconnection network design(s) tailored to their performance needs and power/silicon area constraints with respect to a range of applications that the system will run. Polaris explores the plethora of NoC designs based on projections of network traffic, architectures, and process characteristics. While Polaris's toolchain is extensible so new traffic, network designs, and technology processes can be added, the current version already incorporates 7872 NoC design points. Polaris is rapid, efficiently iterating over thousands of NoC design points, while maintaining high relative and absolute accuracies when validated against detailed NoC synthesis results.

Technology trends are driving parallel on-chip architectures in the form of multi-processor systems-on-a-chip (MPSoCs) and chip multi-processors (CMPs). In these systems the increasing on-chip communication demand among the computation elements necessitates the use of scalable, nigh-bandwidth network-on-chip (NoC) fabrics. As transistor feature sizes are further miniaturized leading to rapidly increasing amounts of on-chip resources, more complicated and powerful NoC architectures become feasible that can support more sophisticated and demanding applications. Given the myriad emerging software-hardware combinations, for cost-effectiveness, a system designer critically needs to prune this widening NoC design space to identify the architecture(s) that best balance(s) cost/performance, before the actual design process begins. This prompted us to develop Polaris 1, a system-level roadmap for on-chip interconnection networks that guides designers towards the most suitable network design(s) tailored to their performance needs and power/silicon area constraints with respect to a range of applications that will run over this network(s). Polaris explores the plethora of NoC designs based on projections of network traffic, architectures, and process characteristics. While the Polaris roadmapping toolchain is extensible so new traffic, network designs, and processes can be added, the current version of the roadmap already incorporates 7,872 NoC design points. Polaris is rapid and iterates over all these NoC architectures within a tractable run time of 125 hours on a typical desktop machine, while maintaining high relative and absolute accuracies when validated against detailed NoC synthesis results.

Network traffic modeling is a critical first step towards understanding and unraveling network power/performancerelated issues. Extensive prior research in the area of classic networks such as the Internet, Ethernet, and wireless LANs transporting TCP/IP, HTTP, and FTP traffic among others, has demonstrated how traffic models and model-based synthetic traffic generators can facilitate understanding of traffic characteristics and drive early-stage simulation to explore a large network design space. Though on-chip networks (a.k.a networks-on-chip (NoCs)) are becoming the de-facto scalable communication fabric in many-core systems-on-a-chip (SoCs) and chip multiprocessors (CMPs), no on-chip network traffic model that captures both spatial and temporal variations of traffic has been demonstrated yet. As available on-chip resources increase with technology scaling, enabling a myriad of new network architectures, NoCs need to be designed from the application’s perspective. In this paper we propose such an empirically-derived network on-chip traffic model for homogeneous NoCs. Our comprehensive model is based on three statistical parameters described with a 3-tuple, and captures the spatio-temporal characteristics of NoC traffic accurately with less than 5% error when compared to actual NoC application traces gathered from fullsystem simulations of three different chip platforms. We illustrate two potential uses of our traffic model: how it allows us to characterize and gain insights on NoC traffic patterns, and how it can be used to generate synthetic traffic traces that can drive NoC design-space exploration.

As packet-switching interconnection networks replace buses and dedicated wires to become the standard on-chip interconnection fabric, reducing their power consumption has been identified to be a major design challenge. Network topologies have high impact on network power consumption. Technology scaling is another important factor that affects network power, since each new technology changes semiconductor physical properties. These two aspects need to be considered synergistically. We characterize the impact of process technologies on network energy for a range of topologies, starting from 2-dimensional meshes/tori, to variants of meshes/tori that incorporate higher dimensions, multiple hierarchies and express channels. We present a method which uses an analytical model to predict the most energy-efficient topology based on network size and architecture parameters for future technologies. Our model is validated against cycle-accurate network power simulation and shown to arrive at the same predictions. We also show how our method can be applied to actual parallel benchmarks with a case study. We see this work as a starting point for defining a roadmap of future on-chip networks.

As demand for bandwidth increases in systems-on-a-chip and chip multiprocessors, networks are fast replacing buses and dedicated wires as the pervasive interconnect fabric for on-chip communication. The tight delay requirements faced by on-chip networks have resulted in prior microarchitectures being largely performance-driven. While performance is a critical metric, on-chip networks are also extremely power-constrained. In this paper, we investigate on-chip network microarchitectures from a power-driven perspective. We first analyze the power dissipation of existing network microarchitectures, highlighting insights that prompt us to devise several power-efficient network microarchitectures: segmented crossbar, cut-through crossbar and write-through buffer. We also study and uncover the power saving potential of existing network architecture: express cube. These techniques are evaluated with synthetic as well as real chip multiprocessor traces, showing a reduction in network power of up to 44.9%, along with no degradation in network performance, and even improved latency-throughput in some cases.

We present Orion, a power-performance interconnection network simulator that is capable of providing detailed power characteristics, in addition to performance characteristics, to enable rapid power-performance tradeoffs at the architectural-level. This capability is provided within a general framework that builds a simulator starting from a microarchitectural specification of the interconnection network. A key component of this construction is the architectural-level parameterized power models that we have derived as part of this effort. Using component power models and a synthesized efficient power (and performance) simulator a microarchitect can rapidly explore the design space. As case studies, we demonstrate the use of Orion in determining optimal system parameters, in examining the effect of diverse traffic conditions, as well as evaluating new network microarchitectures. In each of the above, the ability to simultaneously monitor power and performance is key in determining suitable microarchitectures.