Energy Efficient Mapping in 3D Mesh Communication Architecture for NoC

By the end of this decade we will be entering into the era of thousand cores SoCs. 3D integration technologies have opened the door of new opportunities for NoC architecture design in SoCs providing higher efficiency compared to 2D integration by appropriately adjusting the increased path lengths of 2D NoC. The application to core mapping on NoC architecture can significantly affect the amount of system's dynamic communication energy consumption. The considerable amount of energy savings can be achieved by appropriately optimizing the application to core mapping in NoC architecture. This paper presents a Branch-and-Bound heuristic for smart application to core mapping in 3D Mesh NoC architecture. Experimental results show that proposed heuristic saves about 42%-55% and 19%-28% of dynamic communication energy consumption in comparison to random mapping in 3D NoC communication architecture and the energy aware-mapping in 2D NoC architecture of same size, respectively

Task mapping and mesh topology exploration for an FPGA-based network on chip

International audienceTask mapping strategies on NoC (Network-on-Chip) have a huge impact on the timing performance and power consumption. So does the to-pology. In this paper, we describe the exploration flow of task mapping algorithms using different NoC mesh shapes. The flow is used to evaluate timing and energy consumption based on a NoC emulation platform. It is open to any task mapping algorithms and to any shapes of NoC mesh. A heterogeneous (PC and FPGA) platform is used to fully perform each step of the flow. The experiments demonstrate that the most appropriate task mapping strategy and the most suitable NoC shape strongly depend on the algorithm used. Depending on the timing latency results obtained and the FPGA resources used, the designer can select the appropriate task mapping strategy on the suitable shape in a short exploration time and with precise timing evaluation

A survey on scheduling and mapping techniques in 3D Network-on-chip

Network-on-Chips (NoCs) have been widely employed in the design of multiprocessor system-on-chips (MPSoCs) as a scalable communication solution. NoCs enable communications between on-chip Intellectual Property (IP) cores and allow those cores to achieve higher performance by outsourcing their communication tasks. Mapping and Scheduling methodologies are key elements in assigning application tasks, allocating the tasks to the IPs, and organising communication among them to achieve some specified objectives. The goal of this paper is to present a detailed state-of-the-art of research in the field of mapping and scheduling of applications on 3D NoC, classifying the works based on several dimensions and giving some potential research directions

The Chameleon Architecture for Streaming DSP Applications

We focus on architectures for streaming DSP applications such as wireless baseband processing and image processing. We aim at a single generic architecture that is capable of dealing with different DSP applications. This architecture has to be energy efficient and fault tolerant. We introduce a heterogeneous tiled architecture and present the details of a domain-specific reconfigurable tile processor called Montium. This reconfigurable processor has a small footprint (1.8 mm$^2$ in a 130 nm process), is power efficient and exploits the locality of reference principle. Reconfiguring the device is very fast, for example, loading the coefficients for a 200 tap FIR filter is done within 80 clock cycles. The tiles on the tiled architecture are connected to a Network-on-Chip (NoC) via a network interface (NI). Two NoCs have been developed: a packet-switched and a circuit-switched version. Both provide two types of services: guaranteed throughput (GT) and best effort (BE). For both NoCs estimates of power consumption are presented. The NI synchronizes data transfers, configures and starts/stops the tile processor. For dynamically mapping applications onto the tiled architecture, we introduce a run-time mapping tool

Energy consumption in networks on chip : efficiency and scaling

Computer architecture design is in a new era where performance is increased by replicating processing cores on a chip rather than making CPUs larger and faster. This design strategy is motivated by the superior energy efficiency of the multi-core architecture compared to the traditional monolithic CPU. If the trend continues as expected, the number of cores on a chip is predicted to grow exponentially over time as the density of transistors on a die increases. A major challenge to the efficiency of multi-core chips is the energy used for communication among cores over a Network on Chip (NoC). As the number of cores increases, this energy also increases, imposing serious constraints on design and performance of both applications and architectures. Therefore, understanding the impact of different design choices on NoC power and energy consumption is crucial to the success of the multi- and many-core designs. This dissertation proposes methods for modeling and optimizing energy consumption in multi- and many-core chips, with special focus on the energy used for communication on the NoC. We present a number of tools and models to optimize energy consumption and model its scaling behavior as the number of cores increases. We use synthetic traffic patterns and full system simulations to test and validate our methods. Finally, we take a step back and look at the evolution of computer hardware in the last 40 years and, using a scaling theory from biology, present a predictive theory for power-performance scaling in microprocessor systems

Towards Optimal Application Mapping for Energy-Efficient Many-Core Platforms

Siirretty Doriast

Energy Efficient Branch and Bound based On-Chip Irregular Network Design

Here we present a technique which construct the topology for heterogeneous SoC, (Application Specific NoC) such that total Dynamic communication energy is optimized. The topology is certain to satisfy the constraints of node degree as well the link length. We first layout the topology by finding the shortest path between traffic characteristics with the branch and bound optimization technique. Deadlock is dealt with escape routing using Spanning tree. Investigation outcome show that the proposed design methodology is fast and achieves significant dynamic energy gain

Low Power Processor Architectures and Contemporary Techniques for Power Optimization – A Review

The technological evolution has increased the number of transistors for a given die area significantly and increased the switching speed from few MHz to GHz range. Such inversely proportional decline in size and boost in performance consequently demands shrinking of supply voltage and effective power dissipation in chips with millions of transistors. This has triggered substantial amount of research in power reduction techniques into almost every aspect of the chip and particularly the processor cores contained in the chip. This paper presents an overview of techniques for achieving the power efficiency mainly at the processor core level but also visits related domains such as buses and memories. There are various processor parameters and features such as supply voltage, clock frequency, cache and pipelining which can be optimized to reduce the power consumption of the processor. This paper discusses various ways in which these parameters can be optimized. Also, emerging power efficient processor architectures are overviewed and research activities are discussed which should help reader identify how these factors in a processor contribute to power consumption. Some of these concepts have been already established whereas others are still active research areas. © 2009 ACADEMY PUBLISHER

Clustering-Based Simultaneous Task and Voltage Scheduling for NoC Systems

Network-on-Chip (NoC) is emerging as a promising communication structure, which is scalable with respect to chip complexity. Meanwhile, latest chip designs are increasingly leveraging multiple voltage-frequency domains for energy-efficiency improvement. In this work, we propose a simultaneous task and voltage scheduling algorithm for energy minimization in NoC based designs. The energy-latency tradeoff is handled by Lagrangian relaxation. The core algorithm is a clustering based approach which not only assigns voltage levels and starting time to each task (or Processing Element) but also naturally finds voltage-frequency clusters. Compared to a recent previous work, which performs task scheduling and voltage assignment sequentially, our method leads to an average of 20 percent energy reduction