Unifying mesh- and tree-based programmable interconnect

We examine the traditional, symmetric, Manhattan mesh design for field-programmable gate-array (FPGA) routing along with tree-of-meshes (ToM) and mesh-of-trees (MoT) based designs. All three networks can provide general routing for limited bisection designs (Rent's rule with p<1) and allow locality exploitation. They differ in their detailed topology and use of hierarchy. We show that all three have the same asymptotic wiring requirements. We bound this tightly by providing constructive mappings between routes in one network and routes in another. For example, we show that a (c,p) MoT design can be mapped to a (2c,p) linear population ToM and introduce a corner turn scheme which will make it possible to perform the reverse mapping from any (c,p) linear population ToM to a (2c,p) MoT augmented with a particular set of corner turn switches. One consequence of this latter mapping is a multilayer layout strategy for N-node, linear population ToM designs that requires only /spl Theta/(N) two-dimensional area for any p when given sufficient wiring layers. We further show upper and lower bounds for global mesh routes based on recursive bisection width and show these are within a constant factor of each other and within a constant factor of MoT and ToM layout area. In the process we identify the parameters and characteristics which make the networks different, making it clear there is a unified design continuum in which these networks are simply particular regions

Efficient Interconnection Schemes for VLSI and Parallel Computation

This thesis is primarily concerned with two problems of interconnecting components in VLSI technologies. In the first case, the goal is to construct efficient interconnection networks for general-purpose parallel computers. The second problem is a more specialized problem in the design of VLSI chips, namely multilayer channel routing. In addition, a final part of this thesis provides lower bounds on the area required for VLSI implementations of finite-state machines. This thesis shows that networks based on Leiserson\u27s fat-tree architecture are nearly as good as any network built in a comparable amount of physical space. It shows that these universal networks can efficiently simulate competing networks by means of an appropriate correspondence between network components and efficient algorithms for routing messages on the universal network. In particular, a universal network of area A can simulate competing networks with O(lg^3A) slowdown (in bit-times), using a very simple randomized routing algorithm and simple network components. Alternatively, a packet routing scheme of Leighton, Maggs, and Rao can be used in conjunction with more sophisticated switching components to achieve O(lg^2 A) slowdown. Several other important aspects of universality are also discussed. It is shown that universal networks can be constructed in area linear in the number of processors, so that there is no need to restrict the density of processors in competing networks. Also results are presented for comparisons between networks of different size or with processors of different sizes (as determined by the amount of attached memory). Of particular interest is the fact that a universal network built from sufficiently small processors can simulate (with the slowdown already quoted) any competing network of comparable size regardless of the size of processors in the competing network. In addition, many of the results given do not require the usual assumption of unit wire delay. Finally, though most of the discussion is in the two-dimensional world, the results are shown to apply in three dimensions by way of a simple demonstration of general results on graph layout in three dimensions. The second main problem considered in this thesis is channel routing when many layers of interconnect are available, a scenario that is becoming more and more meaningful as chip fabrication technologies advance. This thesis describes a system MulCh for multilayer channel routing which extends the Chameleon system developed at U. C. Berkeley. Like Chameleon, MulCh divides a multilayer problem into essentially independent subproblems of at most three layers, but unlike Chameleon, MulCh considers the possibility of using partitions comprised of a single layer instead of only partitions of two or three layers. Experimental results show that MulCh often performs better than Chameleon in terms of channel width, total net length, and number of vias. In addition to a description of MulCh as implemented, this thesis provides improved algorithms for subtasks performed by MulCh, thereby indicating potential improvements in the speed and performance of multilayer channel routing. In particular, a linear time algorithm is given for determining the minimum width required for a single-layer channel routing problem, and an algorithm is given for maintaining the density of a collection of nets in logarithmic time per net insertion. The last part of this thesis shows that straightforward techniques for implementing finite-state machines are optimal in the worst case. Specifically, for any s and k, there is a deterministic finite-state machine with s states and k symbols such that any layout algorithm requires (ks lg s) area to lay out its realization. For nondeterministic machines, there is an analogous lower bound of (ks^2) area

Efficient parallel processing with optical interconnections

With the advances in VLSI technology, it is now possible to build chips which can each contain thousands of processors. The efficiency of such chips in executing parallel algorithms heavily depends on the interconnection topology of the processors. It is not possible to build a fully interconnected network of processors with constant fan-in/fan-out using electrical interconnections. Free space optics is a remedy to this limitation. Qualities exclusive to the optical medium are its ability to be directed for propagation in free space and the property that optical channels can cross in space without any interference. In this thesis, we present an electro-optical interconnected architecture named Optical Reconfigurable Mesh (ORM). It is based on an existing optical model of computation. There are two layers in the architecture. The processing layer is a reconfigurable mesh and the deflecting layer contains optical devices to deflect light beams. ORM provides three types of communication mechanisms. The first is for arbitrary planar connections among sets of locally connected processors using the reconfigurable mesh. The second is for arbitrary connections among N of the processors using the electrical buses on the processing layer and N2 fixed passive deflecting units on the deflection layer. The third is for arbitrary connections among any of the N2 processors using the N2 mechanically reconfigurable deflectors in the deflection layer. The third type of communication mechanisms is significantly slower than the other two. Therefore, it is desirable to avoid reconfiguring this type of communication during the execution of the algorithms. Instead, the optical reconfiguration can be done before the execution of each algorithm begins. Determining a right configuration that would be suitable for the entire configuration of a task execution is studied in this thesis. The basic data movements for each of the mechanisms are studied. Finally, to show the power of ORM, we use all three types of communication mechanisms in the first O(logN) time algorithm for finding the convex hulls of all figures in an N x N binary image presented in this thesis

Mesh-of-Trees Interconnection Network for an Explicitly Multi-Threaded Parallel Computer Architecture

As the multiple-decade long increase in clock rates starts to slow down, main-stream general-purpose processors evolve towards single-chip parallel processing. On-chip interconnection networks are essential components of such machines, supporting the communication between processors and the memory system. This task is especially challenging for some easy-to-program parallel computers, which are designed with performance-demanding memory systems. This study proposes an interconnection network, with a novel implementation of the Mesh-of-Trees (MoT) topology. The MoT network is evaluated relative to metrics such as wire area complexity, total register count, bandwidth, network diameter, single switch delay, maximum throughput per area, trade-offs between throughput and latency, and post-layout performance. It is also compared with some other traditional network topologies, such as mesh, ring, hypercube, butterfly, fat trees, butterfly fat trees, and replicated butterfly networks. Concrete results show that MoT provides higher throughput and lower latency especially when the input traffic (or the on-chip parallelism) is high, at comparable area cost. The layout of MoT network is evaluated using standard cell design methodology. A prototype chip with 8-terminal MoT network was taped out at $90nm$ technology and tested. In the context of an easy-to-program single-chip parallel processor, MoT network is embedded in the eXplicit Multi-Threading (XMT) architecture, and evaluated by running parallel applications. In addition to the basic MoT architecture, a novel hybrid extension of MoT is proposed, which allows significant area savings with a small reduction in throughput

A study on hardware design for high performance artificial neural network by using FPGA and NoC

制度:新 ; 報告番号:甲3421号 ; 学位の種類:博士(工学) ; 授与年月日:2011/9/15 ; 早大学位記番号:新574

Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing

The development of computing systems based on the conventional von Neumann architecture has slowed down in the past decade as complementary metal-oxide-semiconductor (CMOS) technology scaling becomes more and more difficult. To satisfy the ever-increasing demands in computing power, neuromorphic computing has emerged as an attractive alternative. This dissertation focuses on developing learning algorithm, hardware architecture, circuit components, and design methodologies for low-power neuromorphic computing that can be employed in various energy-constrained applications. A top-down approach is adopted in this research. Starting from the algorithm-architecture co-design, a hardware-friendly learning algorithm is developed for spiking neural networks (SNNs). The possibility of estimating gradients from spike timings is explored. The learning algorithm is developed for the ease of hardware implementation, as well as the compatibility with many well-established learning techniques developed for classic artificial neural networks (ANNs). An SNN hardware equipped with the proposed on-chip learning algorithm is implemented in CMOS technology. In this design, two unique features of SNNs, the event-driven computation and the inferring with a progressive precision, are leveraged to reduce the energy consumption. In addition to low-power SNN hardware, accelerators for ANNs are also presented to accelerate the adaptive dynamic programing algorithm. An efficient and flexible single-instruction-multiple-data architecture is proposed to exploit the inherent data-level parallelism in the inference and learning of ANNs. In addition, the accelerator is augmented with a virtual update technique, which helps improve the throughput and energy efficiency remarkably. Lastly, two techniques in the architecture-circuit level are introduced to mitigate the degraded reliability of the memory system in a neuromorphic hardware owing to the aggressively-scaled supply voltage and integration density. The first method uses on-chip feedback to compensate for the process variation and the second technique improves the throughput and energy efficiency of a conventional error-correction method.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144149/1/zhengn_1.pd

Area and Energy Opimized QCA Based Shuffle-Exchange Network with Multicast and Broadcast Configuration

In any wide-range processing system, rapid interconnecting networks are employed between the processing modules and embedded systems. This study deals with the optimized design and implementation of Switching Element (SE) which operates in four modes, accepting two inputs and delivering two outputs. The Shuffle-Exchange Network (SEN) can be used as a single-stage as well as a multi-stage network. SEN is used as an interconnection architecture which is implemented with exclusive input-output paths with simple design. The SE acts as a building block to the Multi-stage Shuffle-Exchange Network (M-SEN) with facilities to perform unicast and multicast operation on the inputs. An 8x8 M-SEN model is also implemented, which works in three modes of communication, termed as "One-to-One", "One-to-Many" and "One-to-All" M-SEN configuration. All the QCA circuits have been implemented and simulated using CAD tool QCADesigner. The proposed QCA-based M-SEN design is better in terms of area occupied by 14.63%, average energy dissipation by 22.75% and cell count with a reduction of 84 cells when compared to reference M-SEN architecture. The optimization of the design in terms of cell count and area results in lesser energy dissipation and hence can be used in future-generation complex networks and communication systems

Network-on-Chip Synchronization

Technology scaling has enabled the number of cores within a System on Chip (SoC) to increase significantly. Globally Asynchronous Locally Synchronous (GALS) systems using Dynamic Voltage and Frequency Scaling (DVFS) operate each of these cores on distinct and dynamic clock domains. The main communication method between these cores is increasingly more likely to be a Network-on-Chip (NoC). Typically, the interfaces between these clock domains experience multi-cycle synchronization latencies due to their use of “brute-force” synchronizers. This dissertation aims to improve the performance of NoCs and thereby SoCs as a whole by reducing this synchronization latency. First, a survey of NoC improvement techniques is presented. One such improvement technique: a multi-layer NoC, has been successfully simulated. Given how one of the most commonly used techniques is DVFS, a thorough analysis and simulation of brute-force synchronizer circuits in both current and future process technologies is presented. Unfortunately, a multi-cycle latency is unavoidable when using brute-force synchronizers, so predictive synchronizers which require only a single cycle of latency have been proposed. To demonstrate the impact of these predictive synchronizer circuits at a high level, multi-core system simulations incorporating these circuits have been completed. Multiple forms of GALS NoC configurations have been simulated, including multi-synchronous, NoC-synchronous, and single-synchronizer. Speedup on the SPLASH benchmark suite was measured to directly quantify the performance benefit of predictive synchronizers in a full system. Additionally, Mean Time Between Failures (MTBF) has been calculated for each NoC synchronizer configuration to determine the reliability benefit possible when using predictive synchronizers