A PRACTICAL PLATFORM FOR CREW EMULATION

1993 ◽  
Vol 03 (02) ◽  
pp. 139-145 ◽  
Author(s):  
PETER J. LOOGES ◽  
STEPHAN OLARIU
Keyword(s):  
Lower Bounds ◽  
Random Access ◽  
Technology Support ◽  
Development Tool ◽  
Pram Model ◽  
Vlsi Technology ◽  
Crew Pram ◽  
Cmos Vlsi ◽  
Parallel Random Access Machine ◽  
Crossbar Network

The Parallel Random Access Machine or PRAM model, has been a much employed parallel algorithm development tool for a number of years. As such, many important problems have been solved on this model. Accordingly, considerable attention has been given to the process of simulating PRAM models on more realistic architectures. The purpose of this paper is to present an efficient simulation of the Concurrent Read Exclusive Write PRAM model by the crossbar connected machine (CCM). In addition to simulation, it is proven that all lower bounds for the CREW PRAM directly apply to the CCM. This is the first presentation of algorithmic lower bounds for a crossbar based model. The buses of the network are assumed to have a broadcast delay of δ(n). Recent implementations of the crossbar network in CMOS VLSI technology support the viability of the CCM model. It is the communication flexibility of the crossbar network which supports the PRAM simulations in a very straightforward manner without the complex interconnection systems or high overhead algorithms of many prior simulations.

ON THE PERFORMANCE AND COST OF SOME PRAM MODELS ON CMP HARDWARE

2010 ◽  
Vol 21 (03) ◽  
pp. 387-404 ◽  
Author(s):  
MARTTI FORSELL
Keyword(s):  
Random Access ◽  
Chip Multiprocessor ◽  
Pram Model ◽  
Vlsi Technology ◽  
Cost Efficient ◽  
Performance Area ◽  
And Performance ◽  
On Chip ◽  
Parallel Random Access Machine ◽  
The Cost

The Parallel Random Access Machine is a very strong model of parallel computing that has resisted cost-efficient implementation attempts for decades. Recently, the development of VLSI technology has provided means for indirect on-chip implementation, but there are different variants of the PRAM model that provide different performance, area and power figures and it is not known how their implementations compare to each others. In this paper we measure the performance and estimate the cost of practical implementations of four PRAM models including EREW, Limited Arbitrary CRCW, Full Arbitrary CRCW, Full Arbitrary Multioperation CRCW on our Eclipse chip multiprocessor framework. Interestingly, the most powerful model shows the lowest simulation cost and highest performance/area and performance/power figures.

Transforming comparison model lower bounds to the parallel-random-access-machine

1997 ◽  
Vol 62 (2) ◽  
pp. 103-110 ◽  
Author(s):  
Dany Breslauer ◽  
Artur Czumaj ◽  
Devdatt P. Dubhashi ◽  
Friedhelm Meyer auf der Heide
Keyword(s):  
Lower Bounds ◽  
Random Access ◽  
Comparison Model ◽  
Random Access Machine ◽  
Parallel Random Access Machine

PARALLEL ALGORITHMS FOR SOME DOMINANCE PROBLEMS BASED ON THE PRAM MODEL

1993 ◽  
Vol 03 (04) ◽  
pp. 367-382
Author(s):  
I.W. CHAN ◽  
D.K. FRIESEN
Keyword(s):  
Computational Model ◽  
Single Point ◽  
Random Access ◽  
Geometric Algorithms ◽  
Counting Problem ◽  
Erew Pram ◽  
Pram Model ◽  
Input Size ◽  
Parallel Random Access Machine ◽  
Direct Dominance

Two parallel geometric algorithms based on the idea of point domination are presented. The first algorithm solves the d-dimensional isothetic rectangles intersection counting problem of input size N/2d, where d>1 and N is a multiple of 2d, in O( log d−1 N) time and O(N log N) space. The second algorithm solves the direct dominance reporting problem for a set of N points in the plane in O( log N+J) time and O(N log N) space, where J denotes the maximum of the number of direct dominances reported by any single point in the set. Both algorithms make use of the EREW PRAM (Exclusive Read Exclusive Write Parallel Random Access Machine) consisting of O(N) processors as the computational model.

scholarly journals Transforming Comparison Model Lower Bounds to the PRAM

1995 ◽  
Vol 2 (10) ◽  
Author(s):  
Dany Breslauer ◽  
Devdatt P. Dubhashi
Keyword(s):  
Decision Tree ◽  
Lower Bounds ◽  
Random Access ◽  
Decision Tree Model ◽  
Tree Model ◽  
Machine Model ◽  
Comparison Model ◽  
Random Access Machine ◽  
Input Domain ◽  
Parallel Random Access Machine

This note provides general transformations of lower bounds in Valiant's<br />parallel comparison decision tree model to lower bounds in the priority<br />concurrent-read concurrent-write parallel-random-access-machine model.<br />The proofs rely on standard Ramsey-theoretic arguments that simplify<br />the structure of the computation by restricting the input domain. The<br />transformation of comparison model lower bounds, which are usually easier<br />to obtain, to the parallel-random-access-machine, unifies some known<br />lower bounds and gives new lower bounds for several problems.

scholarly journals PRAM MEMORY ALLOCATION AND INITIALIZATION

1993 ◽  
Vol 03 (03) ◽  
pp. 291-299 ◽  
Author(s):  
LISA HIGHAM ◽  
ERIC SCHENK
Keyword(s):  
Random Access ◽  
Constant Factor ◽  
The Other ◽  
Memory Allocation ◽  
Random Access Machine ◽  
Erew Pram ◽  
Crew Pram ◽  
Parallel Random Access Machine

Two techniques for managing memory on a parallel random access machine (PRAM) are presented. One is a scheme for an n/log n processor EREW PRAM that dynamically allocates and deallocates up to n records of the same size in O(log n) time. The other is a simulation of a PRAM with initialized memory by one with uninitialized memory. A CREW PRAM variant of the technique justifies the assumption that memory can be assumed to be appropriately initialized with no asymptotic increase in time but a factor of n increase in space. An EREW PRAM solution incurs a factor of O(log n) increase in time but only a constant factor increase in space.

scholarly journals Lower Bounds for Dynamic Transitive Closure, Planar Point Location, and Parentheses Matching

1996 ◽  
Vol 3 (9) ◽  
Author(s):  
Thore Husfeldt ◽  
Theis Rauhe ◽  
Søren Skyum
Keyword(s):  
Lower Bound ◽  
Lower Bounds ◽  
Transitive Closure ◽  
Unit Cost ◽  
Random Access ◽  
Point Location ◽  
Worst Case ◽  
Planar Point ◽  
Planar Point Location ◽  
Prefix Sums

We give a number of new lower bounds in the cell probe model<br />with logarithmic cell size, which entails the same bounds on the random access computer with logarithmic word size and unit cost operations. We study the signed prefix sum problem: given a string of length n of zeroes and signed ones, compute the sum of its ith prefix during updates. We show a<br />lower bound of  Omega(log n/log log n) time per operations, even if the prefix sums are bounded by log n/log log n during all updates. We also show that if the update time is bounded by the product of the worst-case update time and the<br />answer to the query, then the update time must be Omega(sqrt(log n/ log log n)).<br /> These results allow us to prove lower bounds for a variety of seemingly unrelated<br />dynamic problems. We give a lower bound for the dynamic planar point location in monotone subdivisions of <br />Omega(log n/ log log n) per operation. We give<br />a lower bound for the dynamic transitive closure problem on upward planar graphs with one source and one sink of <br />Omega(log n/(log logn)^2) per operation. We give a lower bound of  Omega(sqrt(log n/log log n)) for the dynamic membership problem of any Dyck language with two or more letters. This implies the same<br />lower bound for the dynamic word problem for the free group with k generators. We also give lower bounds for the dynamic prefix majority and prefix equality problems.

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