Range Queries in Non-blocking k
... Brown and Helga [9] presented a k-ST in which each internal node has k children, and each leaf contains up to k − 1 keys. For large values of k, this translates into an algorithm which minimizes cache misses and benefits from processor pre-fetching mechanisms. In some ways, the k-ST is similar to a ...
... Brown and Helga [9] presented a k-ST in which each internal node has k children, and each leaf contains up to k − 1 keys. For large values of k, this translates into an algorithm which minimizes cache misses and benefits from processor pre-fetching mechanisms. In some ways, the k-ST is similar to a ...
Comparison of Brute-Force and KD Tree Algorithm
... Abstract: Data mining may be viewed as the extraction of the hidden predictive information from large databases, is a powerful new technology with great potential to analyze important information in the data warehouse. Nearest neighbor search (NNS), also known as proximity search, similarity search ...
... Abstract: Data mining may be viewed as the extraction of the hidden predictive information from large databases, is a powerful new technology with great potential to analyze important information in the data warehouse. Nearest neighbor search (NNS), also known as proximity search, similarity search ...
SPST-Index : A Self Pruning Splay Tree Index for
... This paper is organized, as follows: Section 2 discusses related work. Section 3 presents our proposal. Section 4 depicts our preliminary results. Finally, section 5 discusses future work. ...
... This paper is organized, as follows: Section 2 discusses related work. Section 3 presents our proposal. Section 4 depicts our preliminary results. Finally, section 5 discusses future work. ...
slides - the CLIP Lab
... “Available Parallelism” • How many active nodes can be processed in parallel over time • Profile the algorithm, not the system – Disregard communication/synchronization costs, runtime overheads and locality – Rough upper bound on parallelism ...
... “Available Parallelism” • How many active nodes can be processed in parallel over time • Profile the algorithm, not the system – Disregard communication/synchronization costs, runtime overheads and locality – Rough upper bound on parallelism ...
58131 Data Structures (Spring 2012)
... 16. Consider the following game: N persons are sitting in a circle. The persons are considered in order. Every second one has to leave the circle. Give an algorithm that tells which person remains as the last remaining person. What is its time complexity? For instance, if N = 5, the persons leaves i ...
... 16. Consider the following game: N persons are sitting in a circle. The persons are considered in order. Every second one has to leave the circle. Give an algorithm that tells which person remains as the last remaining person. What is its time complexity? For instance, if N = 5, the persons leaves i ...
Data Structures
... explain the following terms: • root node • path • leaf node • parent node • sibling ...
... explain the following terms: • root node • path • leaf node • parent node • sibling ...
Lecture L16 — April 19, 2012 1 Overview 2 Predecessor Problem
... [l, n], for each i. With the augmentation, this is equivalent to looking for the $i whose stored value is < l, because this indicates that the previous $i is outside of the interval [l, n]. We can solve this problem with an RMQ query from L15. Find the minimum in O(1) time. Suppose the minimum is fo ...
... [l, n], for each i. With the augmentation, this is equivalent to looking for the $i whose stored value is < l, because this indicates that the previous $i is outside of the interval [l, n]. We can solve this problem with an RMQ query from L15. Find the minimum in O(1) time. Suppose the minimum is fo ...
Performance Analysis of BSTs in System Software 1
... as AVL trees, red-black trees, and splay trees, are of- situations, and some reflect worst- and best-case inten used in system software, such as operating system put order for BSTs. kernels. Choosing the right kind of tree can impact performance significantly, but the literature offers few empirical ...
... as AVL trees, red-black trees, and splay trees, are of- situations, and some reflect worst- and best-case inten used in system software, such as operating system put order for BSTs. kernels. Choosing the right kind of tree can impact performance significantly, but the literature offers few empirical ...
Exercise 2
... current_id is in scope in any function invocation resulting from a bulk launch and provides the number of the current invocation. // External function declarations. Your solution may or may not use all these functions. void sort(int count, int* input, int* output); int bin_func(float value); // inpu ...
... current_id is in scope in any function invocation resulting from a bulk launch and provides the number of the current invocation. // External function declarations. Your solution may or may not use all these functions. void sort(int count, int* input, int* output); int bin_func(float value); // inpu ...
Dynamic Tree Cross Products
... data structure described in [12]. It preprocesses a tree in linear time and space such that level ancestor queries and adding leaves can be performed in O(1) worst-case time [12, Theorem 6]. Deleting leaves is not explicitly mentioned in [12], but it is obviously possible in constant time by simply ...
... data structure described in [12]. It preprocesses a tree in linear time and space such that level ancestor queries and adding leaves can be performed in O(1) worst-case time [12, Theorem 6]. Deleting leaves is not explicitly mentioned in [12], but it is obviously possible in constant time by simply ...
Finger trees: a simple general
... Because all leaves of the original 2-3 tree were at the same depth, the left and right spines have the same length, and we can pair corresponding nodes on these spines to make a single central spine. Hanging off the sides of these nodes are 2-3 trees, whose depth increases as we descend the central ...
... Because all leaves of the original 2-3 tree were at the same depth, the left and right spines have the same length, and we can pair corresponding nodes on these spines to make a single central spine. Hanging off the sides of these nodes are 2-3 trees, whose depth increases as we descend the central ...
Indexing Correlated Probabilistic Databases
... Building INDSEP: Variable Renaming • Each node stores all the variables present in its subtree - inefficient • Rename variables so that we can store a range (not sets) • Each partition will have – (min, max) e.g. [4, 7] – add-list e.g. {2} ...
... Building INDSEP: Variable Renaming • Each node stores all the variables present in its subtree - inefficient • Rename variables so that we can store a range (not sets) • Each partition will have – (min, max) e.g. [4, 7] – add-list e.g. {2} ...
CSE 143, Winter 2010 Final Exam Thursday, March 18, 2010
... You must also make StudentTicket objects comparable to each other using the Comparable interface. StudentTickets are compared by price, breaking ties by promotion code. In other words, a StudentTicket object with a lower price is considered to be "less than" one with a higher price. If two tickets h ...
... You must also make StudentTicket objects comparable to each other using the Comparable interface. StudentTickets are compared by price, breaking ties by promotion code. In other words, a StudentTicket object with a lower price is considered to be "less than" one with a higher price. If two tickets h ...
DHTs
... – We can have r different coordinate spaces – Nodes hold a zone in each of them – Creates r replicas of the (key, value) pairs – Increases robustness – Reduces path length as search can be continued in the reality where the target is closest • Overloading zones – Different peers are responsible for ...
... – We can have r different coordinate spaces – Nodes hold a zone in each of them – Creates r replicas of the (key, value) pairs – Increases robustness – Reduces path length as search can be continued in the reality where the target is closest • Overloading zones – Different peers are responsible for ...
Review questions for Chapter 8
... 1. The properties of an abstract data type are tightly related to the implementation of that data type. 2. The two general approaches for implementing a container are array-based and linked implementations. 3. The operations on a list differ depending on the implementation strategy used. 4. A stack ...
... 1. The properties of an abstract data type are tightly related to the implementation of that data type. 2. The two general approaches for implementing a container are array-based and linked implementations. 3. The operations on a list differ depending on the implementation strategy used. 4. A stack ...
Binary search tree
In computer science, binary search trees (BST), sometimes called ordered or sorted binary trees, are a particular type of containers: data structures that store ""items"" (such as numbers, names and etc.) in memory. They allow fast lookup, addition and removal of items, and can be used to implement either dynamic sets of items, or lookup tables that allow finding an item by its key (e.g., finding the phone number of a person by name).Binary search trees keep their keys in sorted order, so that lookup and other operations can use the principle of binary search: when looking for a key in a tree (or a place to insert a new key), they traverse the tree from root to leaf, making comparisons to keys stored in the nodes of the tree and deciding, based on the comparison, to continue searching in the left or right subtrees. On average, this means that each comparison allows the operations to skip about half of the tree, so that each lookup, insertion or deletion takes time proportional to the logarithm of the number of items stored in the tree. This is much better than the linear time required to find items by key in an (unsorted) array, but slower than the corresponding operations on hash tables.They are a special case of the more general B-tree with order equal to two.