Li-Shiuan Peh

Orion: a power-performance simulator for interconnection networks

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.

ORION 2.0: a fast and accurate NoC power and area model for early-stage design space exploration

As industry moves towards many-core chips, networks-on-chip (NoCs) are emerging as the scalable fabric for interconnecting the cores. With power now the first-order design constraint, early-stage estimation of NoC power has become crucially important. ORION was amongst the first NoC power models released, and has since been fairly widely used for early-stage power estimation of NoCs. However, when validated against recent NoC prototypes - the Intel 80-core Teraflops chip and the Intel scalable communications core (SCC) chip - we saw significant deviation that can lead to erroneous NoC design choices. This prompted our development of ORION 2.0, an extensive enhancement of the original ORION models which includes completely new subcomponent power models, area models, as well as improved and updated technology models. Validation against the two Intel chips confirms a substantial improvement in accuracy over the original ORION. A case study with these power models plugged within the COSI-OCC NoC design space exploration tool confirms the need for, and value of, accurate early-stage NoC power estimation. To ensure the longevity of ORION 2.0, we will be releasing it wrapped within a semi-automated flow that automatically updates its models as new technology files become available.

Outstanding Research Problems in NoC Design: System, Microarchitecture, and Circuit Perspectives

To alleviate the complex communication problems that arise as the number of on-chip components increases, network-on-chip (NoC) architectures have been recently proposed to replace global interconnects. In this paper, we first provide a general description of NoC architectures and applications. Then, we enumerate several related research problems organized under five main categories: Application characterization, communication paradigm, communication infrastructure, analysis, and solution evaluation. Motivation, problem description, proposed approaches, and open issues are discussed for each problem from system, microarchitecture, and circuit perspectives. Finally, we address the interactions among these research problems and put the NoC design process into perspective.

Dynamic voltage scaling with links for power optimization of interconnection networks

Originally developed to connect processors and memories in multicomputers, prior research and design of interconnection networks have focused largely on performance. As these networks get deployed in a wide range of new applications, where power is becoming a key design constraint, we need to seriously consider power efficiency in designing interconnection networks. As the demand for network bandwidth increases, communication links, already a significant consumer of power now, will take up an ever larger portion of total system power budget. In this paper we motivate the use of dynamic voltage scaling (DVS) for links, where the frequency and voltage of links are dynamically adjusted to minimize power consumption. We propose a history-based DVS policy that judiciously adjusts link frequencies and voltages based on past utilization. Our approach realizes up to 6.3/spl times/ power savings (4.6/spl times/ on average). This is accompanied by a moderate impact on performance (15.2% increase in average latency before network saturation and 2.5% reduction in throughput.) To the best of our knowledge, this is the first study that targets dynamic power optimization of interconnection networks.

GARNET: A detailed on-chip network model inside a full-system simulator

Until very recently, microprocessor designs were computation-centric. On-chip communication was frequently ignored. This was because of fast, single-cycle on-chip communication. The interconnect power was also insignificant compared to the transistor power. With uniprocessor designs providing diminishing returns and the advent of chip multiprocessors (CMPs) in mainstream systems, the on-chip network that connects different processing cores has become a critical part of the design. Transistor miniaturization has led to high global wire delay, and interconnect power comparable to transistor power. CMP design proposals can no longer ignore the interaction between the memory hierarchy and the interconnection network that connects various elements. This necessitates a detailed and accurate interconnection network model within a full-system evaluation framework. Ignoring the interconnect details might lead to inaccurate results when simulating a CMP architecture. It also becomes important to analyze the impact of interconnection network optimization techniques on full system behavior. In this light, we developed a detailed cycle-accurate interconnection network model (GARNET), inside the GEMS full-system simulation framework. GARNET models a classic five-stage pipelined router with virtual channel (VC) flow control. Microarchitectural details, such as flit-level input buffers, routing logic, allocators and the crossbar switch, are modeled. GARNET, along with GEMS, provides a detailed and accurate memory system timing model. To demonstrate the importance and potential impact of GARNET, we evaluate a shared and private L2 CMP with a realistic state-of-the-art interconnection network against the original GEMS simple network. The objective of the evaluation was to figure out which configuration is better for a particular workload. We show that not modeling the interconnect in detail might lead to an incorrect outcome. We also evaluate Express Virtual Channels (EVCs), an on-chip network flow control proposal, in a full-system fashion. We show that in improving on-chip network latency-throughput, EVCs do lead to better overall system runtime, however, the impact varies widely across applications.

Research Challenges for On-Chip Interconnection Networks

On-chip interconnection networks are rapidly becoming a key enabling technology for commodity multicore processors and SoCs common in consumer embedded systems, the National Science Foundation initiated a workshop that addressed upcoming research issues in OCIN technology, design, and implementation and set a direction for researchers in the field.

Power-driven design of router microarchitectures in 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.

DSENT - A Tool Connecting Emerging Photonics with Electronics for Opto-Electronic Networks-on-Chip Modeling

With the rise of many-core chips that require substantial bandwidth from the network on chip (NoC), integrated photonic links have been investigated as a promising alternative to traditional electrical interconnects. While numerous opto-electronic NoCs have been proposed, evaluations of photonic architectures have thus-far had to use a number of simplifications, reflecting the need for a modeling tool that accurately captures the tradeoffs for the emerging technology and its impacts on the overall network. In this paper, we present DSENT, a NoC modeling tool for rapid design space exploration of electrical and opto-electrical networks. We explain our modeling framework and perform an energy-driven case study, focusing on electrical technology scaling, photonic parameters, and thermal tuning. Our results show the implications of different technology scenarios and, in particular, the need to reduce laser and thermal tuning power in a photonic network due to their non-data-dependent nature.

Demo: SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory

While traffic signals are necessary to safely control competing flows of traffic, they inevitably enforce a stop-and-go movement pattern that increases fuel consumption, reduces traffic flow and causes traffic jams. These side effects can be alleviated by providing drivers and their onboard computational devices (e.g., vehicle computer, smartphone) with information about the schedule of the traffic signals ahead. Based on when the signal ahead will turn green, drivers can then adjust speed so as to avoid coming to a complete halt. Such information is called Green Light Optimal Speed Advisory (GLOSA). Alternatively, the onboard computational device may suggest an efficient detour that will save the driver from stops and long waits at red lights ahead. This paper introduces and evaluates SignalGuru, a novel software service that relies solely on a collection of mobile phones to detect and predict the traffic signal schedule, enabling GLOSA and other novel applications. Our SignalGuru leverages windshield-mounted phones to opportunistically detect current traffic signals with their cameras, collaboratively communicate and learn traffic signal schedule patterns, and predict their future schedule. Results from two deployments of SignalGuru, using iPhones in cars in Cambridge (MA, USA) and Singapore, show that traffic signal schedules can be predicted accurately. On average, SignalGuru comes within 0.66s, for pre-timed traffic signals and within 2.45s, for traffic-adaptive traffic signals. Feeding SignalGurus predicted traffic schedule to our GLOSA application, our vehicle fuel consumption measurements show savings of 20.3%, on average.

Leakage power modeling and optimization in interconnection networks

Power will be the key limiter to system scalability as interconnection networks take up an increasingly significant portion of system power. In this paper, we propose an architectural leakage power modeling methodology that achieves 95-98% accuracy against HSPICE estimates. When applied to interconnection networks, combined with previous proposed dynamic power models, we gain valuable insights on total network power consumption. Our modeling shows router buffers to be a prime candidate for leakage power optimization. We thus investigate the design space of power-aware buffer policies, propose a suite of policies, and explore the impact of various circuits mechanisms on these policies . Simulations show power-aware buffers saving up to 96.6% of total buffer leakage power.