Multiple Clock Domain (MCD) processors are a promising future alternative to today's fully synchronous designs. Dynamic Voltage and Frequency Scaling (DVFS) in an MCD processor has the extra flexibility to adjust the voltage and frequency in each domain independently.Most existing DVFS approaches are profile-based offline schemes which are mainly suitable for applications whose execution characteristics are constrained and repeatable. While some work has been published about online DVFS schemes, the prior approaches are typically heuristic-based. In this paper, we present an effective online DVFS scheme for an MCD processor which takes a formal analytic approach, is driven by dynamic workloads, and is suitable for all applications.In our approach, we model an MCD processor as a queue-domain network and the online DVFS as a feedback control problem with issue queue occupancies as feedback signals. A dynamic stochastic queuing model is first proposed and linearized through an accurate linearization technique. A controller is then designed and verified by stability analysis. Finally we evaluate our DVFS scheme through a cycle-accurate simulation with a broad set of applications selected from MediaBench and SPEC2000 benchmark suites. Compared to the best-known prior approach, which is heuristicbased, the proposed online DVFS scheme is substantially more effective due to its automatic regulation ability. For example, we have achieved a 2-3 fold increase in efficiency in terms of energy-delay product improvement. In addition, our control theoretic technique is more resilient, requires less tuning effort, and has better scalability as compared to prior online DVFS schemes.We believe that the techniques and methodology described in this paper can be generalized for energy control in processors other than MCD, such as tiled stream processors.

Multiple Clock Domain (MCD) processors are a promising future alternative to today's fully synchronous designs. Dynamic Voltage and Frequency Scaling (DVFS) in an MCD processor has the extra flexibility to adjust the voltage and frequency in each domain independently. Most existing DVFS approaches are profile-based offline schemes which are mainly suitable for applications whose execution char-acteristics are constrained and repeatable. While some work has been published about online DVFS schemes, the prior approaches are typically heuristic-based. In this paper, we present an effective online DVFS scheme for an MCD processor which takes a formal analytic approach, is driven by dynamic workloads, and is suitable for all applications. In our approach, we model an MCD processor as a queue-domain network and the online DVFS as a feedback control problem with issue queue occupancies as feedback signals. A dynamic stochastic queuing model is first proposed and linearized through an accu-rate linearization technique. A controller is then designed and verified by stability analysis. Finally we evaluate our DVFS scheme through a cycle-accurate simulation with a broad set of applications selected from MediaBench and SPEC2000 benchmark suites. Compared to the best-known prior approach, which is heuristic-based, the proposed online DVFS scheme is substantially more effective due to its automatic regulation ability. For example, we have achieved a 2-3 fold increase in efficiency in terms of energy-delay product improvement. In addition, our control theoretic technique is more resilient, requires less tuning effort, and has better scalability as compared to prior online DVFS schemes.We believe that the techniques and methodology described in this paper can be generalized for energy control in processors other than MCD, such as tiled stream processors.

Multiple Clock Domain (MCD) processors are a promising future alternative to today's fully synchronous designs. Dynamic Voltage and Frequency Scaling (DVFS) in an MCD processor has the extra flexibility to adjust the voltage and frequency in each domain independently.Most existing DVFS approaches are profile-based offline schemes which are mainly suitable for applications whose execution characteristics are constrained and repeatable. While some work has been published about online DVFS schemes, the prior approaches are typically heuristic-based. In this paper, we present an effective online DVFS scheme for an MCD processor which takes a formal analytic approach, is driven by dynamic workloads, and is suitable for all applications.In our approach, we model an MCD processor as a queue-domain network and the online DVFS as a feedback control problem with issue queue occupancies as feedback signals. A dynamic stochastic queuing model is first proposed and linearized through an accurate linearization technique. A controller is then designed and verified by stability analysis. Finally we evaluate our DVFS scheme through a cycle-accurate simulation with a broad set of applications selected from MediaBench and SPEC2000 benchmark suites. Compared to the best-known prior approach, which is heuristicbased, the proposed online DVFS scheme is substantially more effective due to its automatic regulation ability. For example, we have achieved a 2-3 fold increase in efficiency in terms of energy-delay product improvement. In addition, our control theoretic technique is more resilient, requires less tuning effort, and has better scalability as compared to prior online DVFS schemes.We believe that the techniques and methodology described in this paper can be generalized for energy control in processors other than MCD, such as tiled stream processors.

Designers are moving toward chip-multiprocessors (CMPs) to leverage application parallelism for higher performance while keeping design complexity under control. However, to date, no power management techniques have been proposed for coordinated power control of multiple processor cores.In this paper, we illustrate how the use of local, per-tile dynamic voltage and frequency scaling (DVFS) techniques can result in tiles counteracting each others' power management policies, significantly hurting chip power-performance. We then propose a coordinated DVFS scheme for CMPs, which eliminates the oscillations and ensures efficient and resilient DVFS control. Specifically, our proposed technique incorporates thread information collected at runtime across the chip. In addition, by extending a control-theoretic local DVFS control technique toward DVFS for chip-multiprocessors, our technique prescribes DVFS settings formally at each tile, thus ensuring stable, distributed, coordinated DVFS control of a CMP. Experimental results show that our technique achieves a 15.5% improvement in energy-delay product over a CMP with no DVFS control, and a 7% improvement in energy-delay product against the latest state-of-the-art local DVFS scheme.

Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The field of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scientific and commercial purposes. This paper examines the research decisions and design tradeoffs that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.The ZebraNet system includes custom tracking collars (nodes) carried by animals under study across a large, wild area; the collars operate as a peer-to-peer network to deliver logged data back to researchers. The collars include global positioning system (GPS), Flash memory, wireless transceivers, and a small CPU; essentially each node is a small, wireless computing device. Since there is no cellular service or broadcast communication covering the region where animals are studied, ad hoc, peer-to-peer routing is needed. Although numerous ad hoc protocols exist, additional challenges arise because the researchers themselves are mobile and thus there is no fixed base station towards which to aim data. Overall, our goal is to use the least energy, storage, and other resources necessary to maintain a reliable system with a very high 'data homing' success rate. We plan to deploy a 30-node ZebraNet system at the Mpala Research Centre in central Kenya. More broadly, we believe that the domain-centric protocols and energy tradeoffs presented here for ZebraNet will have general applicability in other wireless azld sensor applications.

With semiconductor technology advancing toward deep submicron, leakage energy is of increasing concern, especially for large on-chip array structures such as caches and branch predictors. Recent work has suggested that even larger branch predictors can and should be used in order to improve microprocessor performance. A further consideration is that more aggressive branch predictors, especially multiported predictors for multiple branch prediction, may be thermal hot spots, thus further increasing its leakage. Moreover, as the branch predictor holds state that is transient and predictive, elements can be discarded without adverse effect. For these reasons, it is natural to consider applying decay techniques-already shown to reduce leakage energy for caches-to branch-prediction structures.Due to the structural difference between caches and branch predictors, applying decay techniques to branch predictors is not straightforward. This paper explores the strategies for exploiting spatial and temporal locality to make decay effective for bimodal, gshare, and hybrid predictors, as well as the branch target buffer. Furthermore, the predictive behavior of branch predictors steers them towards decay based not on state-preserving, static storage cells, but rather quasi-static, dynamic storage cells. This paper will examine the results of implementing decaying branch predictor structures with dynamic-appropriately, decaying-cells rather than the standard static SRAM cell.Overall, this paper demonstrates that decay techniques can apply to more than just caches, with the branch predictor and BTB as an example. We show decay can either be implemented at the architectural level, or with a wholesale replacement of static storage cells with quasi-static storage cells which naturally implement decay. More importantly, decay techniques can be applied and should be applied to other such transient and/or predictive structures.

Chip multi-processors (CMPs) already have widespread commercial availability, and technology roadmaps project enough on-chip transistors to replicate tens or hundreds of current processor cores. How will we express parallelism, partition applications, and schedule/place/migrate threads on these highly-parallel CMPs?This paper presents and evaluates a new approach to highly-parallel CMPs, advocating a new hardware-software contract. The software layer is encouraged to expose large amounts of multi-granular, heterogeneous parallelism. The hardware, meanwhile, is designed to offer low-overhead, low-area support for orchestrating and modulating this parallelism on CMPs at runtime. Specifically, our proposed CMP architecture consists of architectural and ISA support targeting thread creation, scheduling and context-switching, designed to facilitate effective hardware run-time mapping of threads to cores at low overheads.Dynamic modulation of parallelism provides the ability to respond to run-time variability that arises from dataset changes, memory system effects and power spikes and lulls, to name a few. It also naturally provides a long-term CMP platform with performance portability and tolerance to frequency and reliability variations across multiple CMP generations. Our simulations of a range of applications possessing do-all, streaming and recursive parallellism show speedups of 4-11.5X and energy-delay-product savings of 3.8X, on average, on a 16-core vs. a 1-core system. This is achieved with modest amounts of hardware support that allows for low overheads in thread creation, scheduling and context-switching. In particular, our simulations motivated the need for hardware support, showing that the large thread management overheads of current run-time software systems can lead to up to 6.5X slowdown. The difficulties faced in static scheduling were shown in our simulations with a static scheduling algorithm, fed with oracle profiled inputs suffering up to 107% slowdown compared to NDP's hardware scheduler, due to its inability to handle memory system variabilities. More broadly, we feel that the ideas presented here show promise for scaling to the systems expected in ten years, where the advantages of high transistor counts may be dampened by difficulties in circuit variations and reliability. These issues will make dynamic scheduling and adaptation mandatory; our proposals represent a first step towards that direction.

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