14724226
Adaptive Garbage Collection for Battery-Operated Environments
Energy is an important constraint for battery-operated embedded Java environments. In this work, we show how the garbage collector (GC) can be tuned to reduce the energy consumption of Java applications. In particular, we show the importance of tuning the frequency of invoking GC based on object allocation and garbage creation rates to optimize leakage energy consumption. We reduce the leakage energy by exploiting the supplygated leakage power optimization that is controlled by the GC. In this mechanism, power supply to memory banks that do not hold any useful data can be shut down. We implement a new adaptive GC mechanism within Sun’s KVM that optimizes the ability to shut down more banks. An evaluation of our approach using various embedded applications shows that the adaptive garbage collection scheme is effective in reducing the system energy consumption across different hardware configurations.
17981801
Studying storage-recomputation tradeoffs in memory-constrained embedded processing
Fueled by an unprecedented desire for convenience and self-service, consumers are embracing embedded technology solutions that enhance their mobile lifestyles. Consequently, we witness an unprecedented proliferation of embedded/mobile applications. Most of the environments that execute these applications have severe power, performance, and memory space constraints that need to be accounted for. In particular, memory limitations can present serious challenges to embedded software designers. The current solutions to this problem include sophisticated packaging techniques and code optimizations for effective memory utilization. While the first solution is not scalable, the second one is restricted by intrinsic data dependences in the code that prevent code restructuring. In this paper, we explore an alternate approach for reducing memory space requirements of embedded applications. The idea is to re-compute the result of a code block (potentially multiple times) instead of storing it in memory and performing a memory operation whenever needed. The main benefit of this approach is that it reduces memory space requirements, that is, no memory space is reserved for storing the result of the code block in question.
17088807
Reducing NoC energy consumption through compiler-directed channel voltage scaling
While scalable NoC (Network-on-Chip) based communication architectures have clear advantages over long point-to-point communication channels, their power consumption can be very high. In contrast to most of the existing hardware-based efforts on NoC power optimization, this paper proposes a compiler-directed approach where the compiler decides the appropriate voltage/frequency levels to be used for each communication channel in the NoC. Our approach builds and operates on a novel graph based representation of a parallel program and has been implemented within an optimizing compiler and tested using 12 embedded benchmarks. Our experiments indicate that the proposed approach behaves better - from both performance and power perspectives - than a hardwarebased scheme and the energy savings it achieves are very close to the savings that could be obtained from an optimal, but hypothetical voltage/frequency scaling scheme.
13530819
Exploiting last idle periods of links for network power management
Network power optimization is becoming increasingly important as the sizes of the data manipulated by parallel applications and the complexity of inter-processor data communications are continuously increasing. Several hardware-based schemes have been proposed in the past for reducing network power consumption, either by turning off unused communication links or by lowering voltage/frequency in links with low usage. While the prior research shows that these schemes can be effective in certain cases, they share the common drawback of not being able to predict the link active and idle times very accurately. This paper, instead, proposes a compiler-based scheme that determines the last use of communication links at each loop nest and inserts explicit link turn-off calls in the application source. Specifically, for each loop nest, the compiler inserts a turn-off call per communication link. Each turned-off link is reactivated upon the next access to it. We automated this approach within a parallelizing compiler and applied it to eight array-intensive embedded applications.
7347899
Data compression for improving SPM behavior
Scratch-pad memories (SPMs) enable fast access to time-critical data. While prior research studied both static and dynamic SPM management strategies, not being able to keep all hot data (i.e., data with high reuse) in the SPM remains the biggest problem. This paper proposes data compression to increase the number of data blocks that can be kept in the SPM. Our experiments with several embedded applications show that our compression-based SPM management heuristic is very effective and outperforms prior static and dynamic SPM management approaches. We also present an ILP formulation of the problem, and show that the proposed heuristic generates competitive results with those obtained through ILP, while spending much less time in compilation.
2552667
An evaluation of code and data optimizations in the context of disk power reduction
Disk power management is becoming increasingly important in high-end server and cluster type of environments that execute data-intensive applications. While hardware-only approaches (e.g., low-power modes supported by current disks) are successful to a certain extent, one also needs to consider the software side to achieve further energy savings. This paper first demonstrates that conventional data locality oriented code transformations are not sufficient for minimizing disk power consumption. The reason is that these optimizations do not take into account how disk-resident array data are laid out on the disk system, and consequently, fail to increase idle periods of disks, which is the primary metric using which disk power can be reduced. Instead, we propose a disk layout aware application optimization strategy that uses both code restructuring and data layout optimization. Our experimental evaluation with several benchmark codes reveal that the proposed strategy is very successful in reducing disk energy consumption without performing much worse than a pure data locality oriented scheme, as far as execution cycles are concerned. The experiments also show that the benefits coming from our approach increase with the increased number of disks; i.e., it scales very well.
21308144
EmoEars: An Emotion Recognition System for Mandarin Speech
In this paper, an emotion recognition system for mandarin speech is presented. Five basic human emotions including angry, fear, happy, neutral and sad are investigated. The recognizer is based on neural network with OCON and ACON architecture. Some novel feature selection methods are also added as optional tool to enhance the efficiency and classification accuracy. The system can train speaker dependent emotion speech model through online emotional utterance recording. Experiment results show that emotion can be recognized through neural network model, the best mean accuracy is 86.7%. In addition, the feature selection module is effective to reduce the compute load and increase the generalization ability of the recognizer.
5706395
Combinatorial Properties of Generalized Hypercube Graphs
This paper investigates combinatorial properties of generalized hypercube graphs including best containers, wide diameter, and fault diameter. These properties have received much attention recently in the study of interconnection networks.
206977606
Priority Based Overlay Multicast for Distributed Interactive Applications
Distributed Interactive Applications (DIAs) is different with other network-based applications, since the data should be delivered to the receiver node according to its priority. Among the existing overlay multicast protocols the "priority-based directed minimum spanning tree" (PST) is designed for DIAs. But in PST the available bandwidth (avail-bw) is used inefficiently and the system becomes unstable when its scale increases. This paper proposed a novel overlay multicast protocol named Priority Based Overlay Multicast (POM), which uses the entities’ priority, links’ delay and node’s avail-bw to build multicast tree. By using POM the nodes with high priority receive the data in short delay, while the nodes with low priority tolerate a long delay in order to balance the available bandwidth usage among the nodes. The simulation results show that POM uses the avail-bw efficiently and keeps the system stable when its scale increases. Keywords: DIAs; Priority; Available bandwidth.
13165468
A note on fragile graphs
In this note, we show that every graph on n vertices and at most 2n - 4 edges contains a vertex-cut S which is also an independent set of G. The result is best possible and answers a question proposed by Caro in the affirmative.
14040084
Divide-and-conquer recurrences associated with generalized heaps, optimal merge, and related structures
An elementary approach is given to studying the recurrence relations associated with generalized heaps (or d-heaps), cost of optimal merge, and generalized divide-and-conquer minimization problems. We derive exact formulae for the solutions of all such recurrences and give some applications. In particular, we present a precise probabilistic analysis of Floyd's algorithm for constructing d-heaps when the input is randomly given. A variant of d-heap having some interesting combinatorial properties is also introduced.