### Table 2. Asymptotic upper bounds for secondary memory structures;; here N = n=B,Logn =log

"... In PAGE 12: ... See [20, 21, 232] for I/O e cient data structures that have been used for answering range searching and related queries. Table2 summarizes the known results on secondary-memory structures for orthogo- nal range searching. The data structure by Subramanian and Ramaswamy [270] for 3- sided queries supports insertion/deletion of a point in time O(Log n +(Log 2 n)=B).... ..."

### Table I. Primary and Secondary Datapath Units for Different Memory Architectures

1999

Cited by 5

### Table 2. Asymptotic upper bounds for secondary memory structures; here N = n=B, Log = logB, and (n) = log log Log n.

1999

"... In PAGE 12: ... See [21, 22, 210] for I/O e cient data structures that have been used for answering range searching and related queries. Table2 summarizes the known results on secondary-memory structures for orthogonal range searching. The data structure by Subramanian and Ramaswamy [240] for 3-sided queries supports insertion/deletion of a point in time O(Log n + Log2 n=B).... ..."

Cited by 205

### Table 2. Asymptotic upper bounds for secondary memory structures; here N = n=B, Log n = logB n, and (n) = log log Log n.

1999

"... In PAGE 12: ... See [20, 21, 232] for I/O e cient data structures that have been used for answering range searching and related queries. Table2 summarizes the known results on secondary-memory structures for orthogo- nal range searching. The data structure by Subramanian and Ramaswamy [270] for 3- sided queries supports insertion/deletion of a point in time O(Log n + (Log2 n)=B).... ..."

Cited by 205

### Table 1: VAMSplit R-tree vs. other structures for secondary memory in varying dimension for exact 21-NN queries on 100K uniformly distributed vectors

1996

Cited by 106

### Table IV. Resources, Time, and Secondary Memory for Solving Several Grand Challenge Problems on a Computer with a PAP of 128 Gflops PAP and RAP of 20 Gflops

1994

Cited by 7

### TABLE 36.2.3 Secondary-memory structures for orthogonal range searching. Here fl(n) = log log logB .

### Table 1: Primary-Secondary example with the number of events on a process bounded by 90.

2005

"... In PAGE 37: ....8GHz clock frequency and 512MB of physical memory. For primary-secondary example, the simulator is run until the number of events on some process reaches 90. The measurements averaged over 300 computations are displayed in Table1 . With computation slicing, for fault-free computations, the slice is always empty.... ..."

Cited by 2

### Table 8 summarizes the known results on secondary-memory structures for orthogonal range searching; here (n) = log log logB n. The data structure by Sub- ramanian and Ramaswamy [106] for 3-sided queries supports insertion/deletion of a point in time O(logB n + (logB n)2=B). Extending the lower-bound proof by Chazelle [43], they also proved that any secondary-memory data structure that an- swers a range-reporting query in time O(logc B n+k=B) requires ((n=B) log(n=B)= log logB n) storage.

1997

Cited by 63