This paper addresses elevator assignment in vertically-partially-connected 3-D-networks-on-chip (NoCs). Elevators are vertical links between dies. Because of yield issues, Through-Silicon-Via (TSV) cost, and heterogeneity in dimension, topology, and technology of different dies, vertically-partially-connected topologies seem unavoidable in the emerging 3-D-NoCs as opposed to fully-connected topologies. In such partially-connected topologies, as there are fewer elevators than routers, the assignment of elevators to routers becomes a new 3-D-specific optimization problem. An improper assignment can lead to dramatic network performance degradation. This paper proposes an elevator assignment method for best-effort wormhole 3-D-NoCs to improve the average network performance. Experimental results show an improvement of about 90% even compared to a greedy (intrinsically good) initial assignment.

Contemporary embedded systems are based on complex heterogeneous multi-core platforms to cater to the increasing number of applications, some of which have (soft) real-time requirements. To reduce cost, resources are shared using diverse arbitration mechanisms, such as Time-Division Multiplexing (TDM), Static-Priority (SP), and Round-Robin (RR), depending on application and resource requirements. However, resource sharing results in interference between sharing applications making it difficult to estimate if the average latency is sufficient to satisfy their real-time requirements. Existing work proposes isolated models that either fail to address the diversity of arbitration mechanisms or cannot capture the dynamic arrival and service processes of applications and resources in multi-core platforms. This paper addresses this problem by proposing a general framework for average-case performance analysis of shared resources in multi-core platforms. The two main contributions are: 1) a general model for resource sharing based on queuing theory that can be used with different arbiters and that captures architectural features of the shared resource, such as pipelining and arbitration delay, and 2) three arbiter models for TDM, SP, and RR, respectively that assume general distributions (G/G/1) and fits within the framework.

This paper addresses link-buffer capacity allocation in the design process of best-effort 3DNoCs holding hotspot memory ports. We show that in 3DSoCs with integrated wide I/O DRAMs, the congestion spreading is different from SoCs with external DRAMs: the bottlenecks are not anymore the external memory ports but the network links that become saturated and retropropagate the congestion. The distribution of bottleneck links is directly affected by the traffic directed to the hot memory ports. Using an analytical performance evaluation method, we determine network link buffer capacities according to the given workload composed of regular and hotspot traffics.

The trend toward integrated many-core architectures makes the network-on-chip (NoC) technology, the on-chip communication infrastructure of choice. However, and as opposed to a simple bus, due to its distributed and complex nature in terms of topology, wire size, routing algorithm, and so on, the timing behavior and thus performance of the infrastructure is difficult to predict. Therefore, one of the important phases in the NoC design flow is performance evaluation, which is to extract performance metrics to verify whether a specific instance from the NoC design space satisfies the requirements of the entire system. In this sense, reducing the time to obtain the NoC performance and consequently speeding-up the design space exploration is one of the keys that can considerably reduce the design-flow time and cost. In an effort toward this direction, we propose in this paper a novel analytical performance evaluation method that can be used in the earliest stages of the design flow, before using time-consuming simulations. The analytical method is used to evaluate the performance of a general purpose NoC and we show that it can predict the router latency, end-to-end per-flow latency, and network saturation point with an accuracy comparable to a cycle-accurate simulation. To systematically analyze the accuracy of our method compared to the corresponding simulation model, we present also an innovative accuracy analysis method.

Today, due to the increasing demand for more and more complex applications in the consumer electronic market segment, Systems-on-Chip consist of many processing elements and become larger and larger. While on-chip system designers must be able to get fast and accurate communication performance analysis for such huge systems, the simulation-based approaches are not adequate anymore. Addressing the increasing need for early performance evaluation in NoC-based system design flow, this paper presents a generic analytical method to estimate communication latencies and link-buffer utilizations for a given NoC architecture with a given application mapped on it. The accuracy of our method is experimentally compared with the results obtained from Cycle-Accurate SystemC simulations.

This paper presents a generic analytical method to estimate communication latency between a source and a destination of a given Network-on-Chip. This method is based on Markov chain stochastic processes. In order to solve the limiting problem of state-space explosion in complex stochastic processes, we propose to construct a reduced Markov chain model for each node of the path, and to recursively use the local mean latencies to obtain the mean latency of the complete path. Comparison between the analytical results obtained by our method and those of a corresponding SystemC CABA simulation platform shows the accuracy of our method.

In order to avoid time-consuming iterations in the design flow of system-on-chip communication, it is required to make early decisions based on the performance estimations of the system. To fulfill such requirements, analytical techniques are fast and reliable alternatives for long and non-exhaustive traditional simulation-based methods. This paper presents a case-study of using an analytical method, based on Markov chain stochastic processes, for latency evaluation of a Network-on-Chip arranged in a two dimensional Mesh topology, with an x-first routing algorithm and an uniform traffic pattern. Results obtained by the analytical method are compared with the results of a Sys-temC simulation platform.

Contemporary embedded systems are based on complex heterogeneous multi-core platforms to cater to the increasing number of applications, some of which have (soft) real-time requirements. To reduce cost, resources are shared using diverse arbitration mechanisms, such as Time-Division Multiplexing (TDM), Static-Priority (SP), and Round-Robin (RR), depending on application and resource requirements. However, resource sharing results in interference between sharing applications making it difficult to estimate if the average latency is sufficient to satisfy their real-time requirements. Existing work proposes isolated models that either fail to address the diversity of arbitration mechanisms or cannot capture the dynamic arrival and service processes of applications and resources in multi-core platforms. This paper addresses this problem by proposing a general framework for average-case performance analysis of shared resources in multi-core platforms. The two main contributions are: 1) a general model for resource sharing based on queuing theory that can be used with different arbiters and that captures architectural features of the shared resource, such as pipelining and arbitration delay, and 2) three arbiter models for TDM, SP, and RR, respectively that assume general distributions (G/G/1) and fits within the framework.