15225704
Dataflow analysis for energy-efficient scratch-pad memory management
Scratch-pad memories (SPMs) are a serious alternative to conventional cache memories in embedded computing since they allow software to manage data flowing from and into memory components, resulting in a predictable behavior at runtime. The prior studies considered compiler-directed SPM management using both static and dynamic approaches. One of the assumptions under which most of the proposed approaches to data SPM management operate is that the application code is structured with regular loop nests with little or no control flow within the loops. This assumption, while it makes data SPM management relatively easy to implement, limits the applicability of those approaches to the codes involve conditional execution and complex control flows. To address this problem, this paper proposes a novel data SPM management strategy based on dataflow analysis. This analysis operates on a representation that reflects the conditional execution flow of the application and, consequently, it is applicable to a large class of embedded applications, including those with complex control flows.
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.
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.
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.
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.
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.
2548796
Four types of lookback
We present a classification that groups lookback into four types: direct strong lookback, universal strong lookback, direct weak lookback, and universal weak lookback. They are defined in terms of absolute and dynamic impact times. We discuss relationships between lookback types by considering when rollbacks and/or antimessages are avoided. From different types of lookback, we also derive three optimization techniques for optimistic simulation and point out their advantages over lazy cancellation. Finally, we show that all four types of lookback exist in the PCS network simulation and can be exploited by either lookback-based or optimistic protocols.
26340659
Combinatorial properties of mesh of trees
A mesh of trees, which has two favorable properties: small diameter and large bisection, is known as the fastest network when considered in terms of speed. We show that the wide diameter, fault diameter, and Rabin number, which are three generalizations of diameter, of a two dimensional 2/sup n//spl times/2/sup n/ mesh of trees are equal to 5n+1.
16806816
Dependency management in distributed settings
Applications in a computation and communication saturated pervasive-computing environment have to adapt their behaviors according the context of the user and the physical space. These "context-aware" applications typically obtain high-level situational understanding by aggregating one or more outputs of distributed sensors. To reduce the complexity of developing and deploying these adaptive applications, we designed and implemented a flexible software infrastructure, Solar, for large-scale context fusion (Chen et al., 2004). Solar consists of a set of functionally equivalent nodes, named Planets, which peer together to form a service overlay. A sensor connects to a Planet to register a name with Solar's naming service and publish a stream of events, while an application connects to a Planet to subscribe to one or more sensor outputs by querying Solar's name space. In addition, applications may inject data-fusion operators into the Solar to reduce the computation and communication costs on the mobile devices. In this paper we present our approach to address the dependency management issues in Solar.
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.
11486473
Circumference of Graphs with Bounded Degree
Karger, Motwani, and Ramkumar Algorithmica, 18 (1997), pp. 82--98] have shown that there is no constant approximation algorithm to find a longest cycle in a Hamiltonian graph, and they conjectured that this is the case even for graphs with bounded degree. On the other hand, Feder, Motwani, and Subi [SIAM J. Comput., 31 (2002), pp. 1596--1607] have shown that there is a polynomial time algorithm for finding a cycle of length $n^{\log_32}$ in a 3-connected cubic n-vertex graph. In this paper, we show that if G is a 3-connected n-vertex graph with maximum degree at most d, then one can find, in O(n3) time, a cycle in G of length at least $\Omega(n^{\log_b2})$, where $b=2(d-1)^2+1$.