Browsing by Subject "Cache memory."

Now showing 1 - 5 of 5

Open Access
Cache locality exploiting methods and models for sparse matrix-vector multiplication
(2009) Akbudak, Kadir
The sparse matrix-vector multiplication (SpMxV) is an important kernel operation widely used in linear solvers. The same sparse matrix is multiplied by a dense vector repeatedly in these solvers to solve a system of linear equations. High performance gains can be obtained if we can take the advantage of today’s deep cache hierarchy in SpMxV operations. Matrices with irregular sparsity patterns make it difficult to utilize data locality effectively in SpMxV computations. Different techniques are proposed in the literature to utilize cache hierarchy effectively via exploiting data locality during SpMxV. In this work, we investigate two distinct frameworks for cacheaware/oblivious SpMxV: single matrix-vector multiply and multiple submatrix-vector multiplies. For the single matrix-vector multiply framework, we propose a cache-size aware top-down row/column-reordering approach based on 1D sparse matrix partitioning by utilizing the recently proposed appropriate hypergraph models of sparse matrices, and a cache oblivious bottom-up approach based on hierarchical clustering of rows/columns with similar sparsity patterns. We also propose a column compression scheme as a preprocessing step which makes these two approaches cache-line-size aware. The multiple submatrix-vector multiplies framework depends on the partitioning the matrix into multiple nonzero-disjoint submatrices. For an effective matrixto-submatrix partitioning required in this framework, we propose a cache-size aware top-down approach based on 2D sparse matrix partitioning by utilizing the recently proposed fine-grain hypergraph model. For this framework, we also propose a traveling salesman formulation for an effective ordering of individual submatrix-vector multiply operations. We evaluate the validity of our models and methods on a wide range of sparse matrices. Experimental results show that proposed methods and models outperforms state-of-the-art schemes.
Open Access
Caching techniques for large scale web search engines
(2011) Özcan, Rıfat
Large scale search engines have to cope with increasing volume of web content and increasing number of query requests each day. Caching of query results is one of the crucial methods that can increase the throughput of the system. In this thesis, we propose a variety of methods to increase the efficiency of caching for search engines. We first provide cost-aware policies for both static and dynamic query result caches. We show that queries have significantly varying costs and processing cost of a query is not proportional to its frequency (popularity). Based on this observation, we develop caching policies that take the query cost into consideration in addition to frequency, while deciding which items to cache. Second, we propose a query intent aware caching scheme such that navigational queries are identified and cached differently from other queries. Query results are cached and presented in terms of pages, which typically includes 10 results each. In navigational queries, the aim is to reach a particular web site which would be typically listed at the top ranks by the search engine, if found. We argue that caching and presenting the results of navigational queries in this 10-per-page manner is not cost effective and thus we propose alternative result presentation models and investigate the effect of these models on caching performance. Third, we propose a cluster based storage model for query results in a static cache. Queries with common result documents are clustered using single link clustering algorithm. We provide a compact storage model for those clusters by exploiting the overlap in query results. Finally, a five-level static cache that consists of all cacheable data items (query results, part of index, and document contents) in a search engine setting is presented. A greedy method is developed to determine which items to cache. This method prioritizes items for caching based on gains computed using items’ past frequency, estimated costs, and storage overheads. This approach alsoconsiders the inter-dependency between items such that caching of an item may affect the gain of items that are not cached yet. We experimentally evaluate all our methods using a real query log and document collections. We provide comparisons to corresponding baseline methods in the literature and we present improvements in terms of throughput, number of cache misses, and storage overhead of query results.
Open Access
Efficient result caching mechanisms in search engines
(2014) Sazoğlu, Fethi Burak
The performance of a search engine depends on its components such as crawler, indexer and processor. The query latency, accuracy and recency of the results play crucial role in determining the performance. High performance can be provided with powerful hardware in the data center, but keeping the operational costs restrained is mandatory for search engines for commercial durability. This thesis focuses on techniques to boost the performance of search engines by means of reducing both the number of queries issued to the backend and the cost to process a query stream. This can be accomplished by taking advantage of the temporal locality of the queries. Caching the result for a recently issued query removes the need to reprocess this query when it is issued again by the same or different user. Therefore, deploying query result cache decreases the load on the resources of the search engine which increases the processing power. The main objective of this thesis is to improve search engine performance by enhancing productivity of result cache. This is done by endeavoring to maximize the cache hit rate and minimizing the processing cost by using the per query statistics such as frequency, timestamp and cost. While providing high hit rates and low processing costs improves performance, the freshness of the queries in the cache has to be considered as well for user satisfaction. Therefore, a variety of techniques are examined in this thesis to bound the staleness of cache results without blasting the backend with refresh queries. The offered techniques are demonstrated to be efficient by using real query log data from a commercial search engine.
Open Access
Replacement problem in Web caching
(2002) Çakıroğlu, Seda
Open Access
A result cache invalidation scheme for web search engines
(2011) Alıcı, Şadiye
The result cache is a vital component for the efficiency of large-scale web search engines, and maintaining the freshness of cached query results is a current research challenge. As a remedy to this problem, our work proposes a new mechanism to identify queries whose cached results are stale. The basic idea behind our mechanism is to maintain and compare the generation time of query results with the update times of posting lists and documents to decide on staleness of query results. The proposed technique is evaluated using a Wikipedia document collection with real update information and a real-life query log. Throughout the experiments, we compare our approach with two baseline strategies from literature together with a detailed evaluation. We show that our technique has good prediction accuracy, relative to the baseline based on the time-to-live (TTL) mechanism. Moreover, it is easy to implement and it incurs less processing overhead on the system relative to a recently proposed, more sophisticated invalidation mechanism.