16525039
Object duplication for improving reliability
Soft errors are becoming a common problem in current systems due to the scaling of technology that results in the use of smaller devices, lower voltages, and power-saving techniques. In this work, we focus on soft errors that can occur in the objects created in heap memory, and investigate techniques for enhancing the immunity to soft errors through various object duplication schemes. The idea is to access the duplicate object when the checksum associated with the primary object indicates an error. We implemented several duplication based schemes and conducted extensive experiments. Our results clearly show that this spectrum of schemes enable us to balance the tradeoffs between error rate and heap space consumption.
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.
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.
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.
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.
27714693
Efficient Parallel Processing for K-Nearest-Neighbor Search in Spatial Databases
Even though the problem of k nearest neighbor (kNN) query is well-studied in serial environment, there is little prior work on parallel kNN search processing in parallel one. In this paper, we present the first Best-First based Parallel kNN (BFPkNN) query algorithm in a multi-disk setting, for efficient handling of kNN retrieval with arbitrary values of k by parallelization. The core of our method is to access more entries from multiple disks simultaneously and enable several effective pruning heuristics to discard non-qualifying entries. Extensive experiments with real and synthetic datasets confirm that BFPkNN significantly outperforms its competitors in both efficiency and scalability.
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.
9256979
Convergence of difference schemes with high resolution for conservation laws
We are concerned with the convergence of Lax-Wendroff type schemes with high resolution to the entropy solutions for conservation laws. These schemes include the original Lax-Wendroff scheme proposed by Lax and Wendroff in 1960 and its two step versions-the Richtmyer scheme and the MacCormack scheme. For the convex scalar conservation laws with algebraic growth flux functions, we prove the convergence of these schemes to the weak solutions satisfying appropriate entropy inequalities. The proof is based on detailed L P estimates of the approximate solutions, H -1 compactness estimates of the corresponding entropy dissipation measures, and some compensated compactness frameworks. Then these techniques are generalized to study the convergence problem for the nonconvex scalar case and the hyperbolic systems of conservation laws.
9764979
Tough enough chordal graphs are Hamiltonian
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.