Work-Efficient Query Evaluation with PRAMs

The paper studies query evaluation in parallel constant time in the PRAM model. While it is well-known that all relational algebra queries can be evaluated in constant time on an appropriate CRCW-PRAM, this paper is interested in the efficiency of evaluation algorithms, that is, in the number of processors or, asymptotically equivalent, in the work. Naive evaluation in the parallel setting results in huge (polynomial) bounds on the work of such algorithms and in presentations of the result sets that can be extremely scattered in memory. The paper first discusses some obstacles for constant time PRAM query evaluation. It presents algorithms for relational operators that are considerably more efficient than the naive approaches. Further it explores three settings, in which efficient sequential query evaluation algorithms exist: acyclic queries, semi-join algebra queries, and join queries - the latter in the worst-case optimal framework. Under natural assumptions on the representation of the database, the work of the given algorithms matches the best sequential algorithms in the case of semi-join queries, and it comes close in the other two settings. An important tool is the compaction technique from Hagerup (1992)

Optimal broadcast on parallel locality models

AbstractIn this paper matching upper and lower bounds for broadcast on general purpose parallel computation models that exploit network locality are proven. These models try to capture both the general purpose properties of models like the PRAM or BSP on the one hand, and to exploit network locality of special purpose models like meshes, hypercubes, etc., on the other hand. They do so by charging a cost l(|i−j|) for a communication between processors i and j, where l is a suitably chosen latency function.An upper bound T(p)=∑i=0loglogp2i·l(p1/2i) on the runtime of a broadcast on a p processor H-PRAM is given, for an arbitrary latency function l(k).The main contribution of the paper is a matching lower bound, holding for all latency functions in the range from l(k)=Ω(logk/loglogk) to l(k)=O(log2k). This is not a severe restriction since for latency functions l(k)=O(logk/log1+εlog(k)) with arbitrary ε>0, the runtime of the algorithm matches the trivial lower bound Ω(logp) and for l(k)=Θ(log1+εk) or l(k)=Θ(kε), the runtime matches the other trivial lower bound Ω(l(p)). Both upper and lower bounds apply for other parallel locality models like Y-PRAM, D-BSP and E-BSP, too

Communication Complexity Lower Bounds by Polynomials

The quantum version of communication complexity allows the two communicating parties to exchange qubits and/or to make use of prior entanglement (shared EPR-pairs). Some lower bound techniques are available for qubit communication complexity, but except for the inner product function, no bounds are known for the model with unlimited prior entanglement. We show that the log-rank lower bound extends to the strongest model (qubit communication + unlimited prior entanglement). By relating the rank of the communication matrix to properties of polynomials, we are able to derive some strong bounds for exact protocols. In particular, we prove both the "log-rank conjecture" and the polynomial equivalence of quantum and classical communication complexity for various classes of functions. We also derive some weaker bounds for bounded-error quantum protocols.Comment: 16 pages LaTeX, no figures. 2nd version: rewritten and some results adde

Fast Computation of Small Cuts via Cycle Space Sampling

We describe a new sampling-based method to determine cuts in an undirected graph. For a graph (V, E), its cycle space is the family of all subsets of E that have even degree at each vertex. We prove that with high probability, sampling the cycle space identifies the cuts of a graph. This leads to simple new linear-time sequential algorithms for finding all cut edges and cut pairs (a set of 2 edges that form a cut) of a graph. In the model of distributed computing in a graph G=(V, E) with O(log V)-bit messages, our approach yields faster algorithms for several problems. The diameter of G is denoted by Diam, and the maximum degree by Delta. We obtain simple O(Diam)-time distributed algorithms to find all cut edges, 2-edge-connected components, and cut pairs, matching or improving upon previous time bounds. Under natural conditions these new algorithms are universally optimal --- i.e. a Omega(Diam)-time lower bound holds on every graph. We obtain a O(Diam+Delta/log V)-time distributed algorithm for finding cut vertices; this is faster than the best previous algorithm when Delta, Diam = O(sqrt(V)). A simple extension of our work yields the first distributed algorithm with sub-linear time for 3-edge-connected components. The basic distributed algorithms are Monte Carlo, but they can be made Las Vegas without increasing the asymptotic complexity. In the model of parallel computing on the EREW PRAM our approach yields a simple algorithm with optimal time complexity O(log V) for finding cut pairs and 3-edge-connected components.Comment: Previous version appeared in Proc. 35th ICALP, pages 145--160, 200

Equality Alone Does not Simulate Randomness

The canonical problem that gives an exponential separation between deterministic and randomized communication complexity in the classical two-party communication model is "Equality". In this work we show that even allowing access to an "Equality" oracle, deterministic protocols remain exponentially weaker than randomized ones. More precisely, we exhibit a total function on n bits with randomized one-sided communication complexity O(log n), but such that every deterministic protocol with access to "Equality" oracle needs Omega(n) cost to compute it. Additionally we exhibit a natural and strict infinite hierarchy within BPP, starting with the class P^{EQ} at its bottom

Assessment of the Utilization of Healthcare Services Specific to Pregnancy-Related Complications In Rural And Medically Underserved Georgia

Maternal mortality is a continuing issue, with rates for the state of Georgia (3.7 per 100,000 live births) are higher than that of the US rates (2.9 per 100,000 per live births) (Centers for Disease Control and Prevention, National Center for Health Statistics, n.d., 2023). However, maternal mortality may not account for health disparity factors, apart from access to quality care and physiological issues, which is a factor in pregnancy-related deaths, Pregnancy-related death, as defined by the US Centers for Disease and Control (CDC), is a death of a woman that occurs during or within one year of pregnancy that can be attributed to a complication, events initiated, or the aggravation of an unrelated condition by the physiologic effects of pregnancy. This mixed data study used secondary data using the Andersen healthcare utilization model to explore factors that may delay early prenatal care utilization in individuals with pre-existing hypertension who live in rural and medically underserved Georgia, which may increase the risk of pregnancy-related complications or death. The quantitative portion of this study did give some insight into the factors of importance that may influence the attainment of early prenatal care visits for individuals with pre-existing hypertension who were of a minority race compared to their white counterparts, regardless of insurance coverage before or during pregnancy particularly seen in individuals of rural county residence. The qualitative portion of this study highlighted some of the ongoing issues, such as support from leadership, changes in practices and policies, among others, and areas for needs of improvement to give adequate care for individuals with pregnancies that are categorized as high-risk in rural communities. Findings from this study will be helpful in setting a foundation for further research to address barriers for individuals with chronic hypertension prior to pregnancy and healthcare utilization