A Compiler-Assisted Scheme for Adaptive Cache Coherence Enforcement

title: Experience in the Automatic Parallelization of Four Perfect-Benchmark Programs
abstract: This paper discusses the techniques used to hand-parallelize, for the Alliant FX/80, four Fortran programs from the Perfect-Benchmark suite. The paper also includes the execution times of the programs before and after the transformations. The four programs considered here were not effectively parallelized by the automatic translators available to the authors. However, most of the techniques used for hand parallelization, and perhaps all of them, have wide applicability and can be incorporated into existing translators.

title: On Reducing Data Synchronization in Multiprocessed Loops
abstract: In this correspondence we present and prove the correctness of an algorithm for reducing the number of synchronized memory references to shared data elements in multiprocessed loops. Optimizing compilers for shared memory multiprocessors can use this algorithm to reduce synchronization overhead. The algorithm has been implemented as a new module in the multiprocessors version of Parafrase, the restructuring system of the University of Illinois. We present a brief discussion of experiments we performed to asses the effectiveness of this algorithm in reducing the synchronization overhead for the 61 subroutines of EISPACK, a package for computing matrix eigenvectors and eigenvalues.

title: New tiling techniques to improve cache temporal locality
abstract: Tiling is a well-known loop transformation to improve temporal locality of nested loops. Current compiler algorithms for tiling are limited to loops which are perfectly nested or can be transformed, in trivial ways, into a perfect nest. This paper presents a number of program transformations to enable tiling for a class of nontrivial imperfectly-nested loops such that cache locality is improved. We define a program model for such loops and develop compiler algorithms for their tiling. We propose to adopt odd-even variable duplication to break anti- and output dependences without unduly increasing the working-set size, and to adopt speculative execution to enable tiling of loops which may terminate prematurely due to, e.g. convergence tests in iterative algorithms. We have implemented these techniques in a research compiler, Panorama. Initial experiments with several benchmark programs are performed on SGI workstations based on MIPS R5K and R10K processors. Overall, the transformed programs run faster by 9% to 164%.

title: Data locality enhancement by memory reduction
abstract: In this paper, we propose memory reduction as a new approach to data locality enhancement. Under this approach, we use the compiler to reduce the size of the data repeatedly referenced in a collection of nested loops. Between their reuses, the data will more likely remain in higher-speed memory devices, such as the cache. Specifically, we present an optimal algorithm to combine loop shifting, loop fusion and array contraction to reduce the temporary array storage required to execute a collection of loops. When applied to 20 benchmark programs, our technique reduces the memory requirement, counting both the data and the code, by 51% on average. The transformed programs gain a speedup of 1.40 on average, due to the reduced footprint and, consequently, the improved data locality.

title: The Cedar System And An Initial Performance Study
abstract: In this paper, we give an overview of the Cedar mutliprocessor and present recent performance results. These include the performance of some computational kernels and the Perfect Benchmarks@ . We also present a methodology f o r judging parallel system performance and apply this methodology to Cedar, Cray YMP-8, and Thinking Machines CM-5.

title: An Interlacing Result on Normalized Laplacians
abstract: Given a graph G, the normalized Laplacian associated with the graph G, denoted ${\cal L}$(G), was introduced by F. R. K. Chung and has been intensively studied in the last 10 years. For a k-regular graph G, the normalized Laplacian ${\cal L}$ (G) and the standard Laplacian matrix L(G) satisfy L(G) = k {\cal L} (G), and hence they have the same eigenvectors and their eigenvalues are directly related. However, for an irregular graph G, ${\cal L} (G) and L(G) behave quite differently, and the normalized Laplacian seems to be more natural. In this paper, Cauchy interlacing-type properties of the normalized Laplacian are investigated, and the following result is established. Let G be a graph, and let H = G - e, where e is an edge of G. Let $\lambda_1\geq \lambda_2 \geq \cdots \geq \lambda_{n}=0$ be the eigenvalues of ${\cal L}(G)$, and let $\theta_1\geq \theta_2 \geq \cdots \geq \theta_{n}$ be the eigenvalues of ${\cal L}(H)$. Then, $\lambda_{k-1} \geq \theta_{k}\geq \lambda_{k+1}$ for each k = 1, 2, 3, \dots, n, where $\lambda_{0} =2$ and $\lambda_{n+1}=0$. Applications are given for eigenvalues of graphs obtained from special graphs by adding or deleting a few edges. A short proof is given of the result that $G$ is a graph with each component a nontrivial bipartite graph if and only if $2-\lambda$ is an eigenvalue of ${\cal L}(G)$ for each eigenvalue $\lambda$ of ${\cal L }(G)$.

title: Fast Video Shot Retrieval with Luminance Field Trace Indexing and Geometry Matching
abstract: Efficient indexing is a key in content-based video retrieval solutions. In this paper we represent video sequences as traces in an appropriate low dimensional space via luminance field scaling and PCA projection, and develop an efficient indexing scheme and trace geometry matching algorithms for fast and robust video retrieval. Simulation results demonstrate that the proposed solution is very fast and accurate in retrieval performance.

title: IDGraphs: intrusion detection and analysis using histographs
abstract: Traffic anomalies and attacks are commonplace in today's networks and identifying them rapidly and accurately is critical for large network operators. For a statistical intrusion detection system (IDS), it is crucial to detect at the flow-level for accurate detection and mitigation. However, existing IDS systems offer only limited support for: 1) interactively examining detected intrusions and anomalies; 2) analyzing worm propagation patterns; 3) and discovering correlated attacks. These problems are becoming even more acute as the traffic on today's high-speed routers continues to grow. IDGraphs is an interactive visualization system for intrusion detection that addresses these challenges. The central visualization in the system is a flow-level trace plotted with time on the horizontal axis and aggregated number of unsuccessful connections on the vertical axis. We then summarize a stack of tens or hundreds of thousands of these traces using the histographs (Pin Ren and Watson, 2005) technique, which maps data frequency at each pixel to brightness. Users may then interactively query the summary view, performing analysis by highlighting subsets of the traces. For example, brushing a linked correlation matrix view highlights traces with similar patterns, revealing distributed attacks that are difficult to detect using standard statistical analysis. We apply IDGraphs system to a real network router data-set with 179M flow-level records representing a total traffic of 1.16TB. The system successfully detects and analyzes a variety of attacks and anomalies, including port scanning, worm outbreaks, stealthy TCP SYN floodings, and some distributed attacks.

title: On achieving maximum multicast throughput in undirected networks
abstract: The transmission of information within a data network is constrained by the network topology and link capacities. In this paper, we study the fundamental upper bound of information dissemination rates with these constraints in undirected networks, given the unique replicable and encodable properties of information flows. Based on recent advances in network coding and classical modeling techniques in flow networks, we provide a natural linear programming formulation of the maximum multicast rate problem. By applying Lagrangian relaxation on the primal and the dual linear programs (LPs), respectively, we derive a) a necessary and sufficient condition characterizing multicast rate feasibility, and b) an efficient and distributed subgradient algorithm for computing the maximum multicast rate. We also extend our discussions to multiple communication sessions, as well as to overlay and ad hoc network models. Both our theoretical and simulation results conclude that, network coding may not be instrumental to achieve better maximum multicast rates in most cases; rather, it facilitates the design of significantly more efficient algorithms to achieve such optimality.

title: Adaptive rate control for H.264
abstract: This paper presents a rate control scheme for H.264 by introducing the concept of basic unit and a linear prediction model. The basic unit can be a macroblock (MB), a slice, or a frame. It can be used to obtain a trade-off between the overall coding efficiency and the bits fluctuation. The linear model is used to solve the chicken and egg dilemma existing in the rate control of H.264. Both constant bit rate (CBR) and variable bit rate (VBR) cases are studied. Our scheme has been adopted by H.264.