Results 1 
5 of
5
Dynamic storage allocation: A survey and critical review
, 1995
"... Dynamic memory allocation has been a fundamental part of most computer systems since roughly 1960, and memory allocation is widely considered to be either a solved problem or an insoluble one. In this survey, we describe a variety of memory allocator designs and point out issues relevant to their de ..."
Abstract

Cited by 210 (6 self)
 Add to MetaCart
Dynamic memory allocation has been a fundamental part of most computer systems since roughly 1960, and memory allocation is widely considered to be either a solved problem or an insoluble one. In this survey, we describe a variety of memory allocator designs and point out issues relevant to their design and evaluation. We then chronologically survey most of the literature on allocators between 1961 and 1995. (Scores of papers are discussed, in varying detail, and over 150 references are given.) We argue that allocator designs have been unduly restricted by an emphasis on mechanism, rather than policy, while the latter is more important; higherlevel strategic issues are still more important, but have not been given much attention. Most theoretical analyses and empirical allocator evaluations to date have relied on very strong assumptions of randomness and independence, but real program behavior exhibits important regularities that must be exploited if allocators are to perform well in practice.
Scalability of Dynamic Storage Allocation Algorithms
, 1996
"... Dynamic storage allocation has a significant impact on computer performance. A dynamic storage allocator manages space for objects whose lifetimes are not known by the system at the time of their creation. A good dynamic storage allocator should utilize storage efficiently and satisfy requests in as ..."
Abstract

Cited by 15 (3 self)
 Add to MetaCart
Dynamic storage allocation has a significant impact on computer performance. A dynamic storage allocator manages space for objects whose lifetimes are not known by the system at the time of their creation. A good dynamic storage allocator should utilize storage efficiently and satisfy requests in as few instructions as possible. A dynamic storage allocator on a multiprocessor should have the ability to satisfy multiple requests concurrently. This paper examines parallel dynamic storage allocation algorithms and how performancescales with increasing numbers of processors. The highest throughputs and lowest instruction counts are achieved with multiple free list fit I. The best memory utilization is achieved using a best fit system.
Fast Allocation and Deallocation with an Improved Buddy System
 IN PROCEEDINGS OF THE 19TH CONFERENCE ON THE FOUNDATIONS OF SOFTWARE TECHNOLOGY AND THEORETICAL COMPUTER SCIENCE (FST & TCS'99), LECTURE NOTES IN COMPUTER SCIENCE
, 1999
"... We propose several modifications to the binary buddy system for managing dynamic allocation of memory blocks whose sizes are powers of two. The standard buddy system allocates and deallocates blocks in \Theta(lg n) time in the worst case (and on an amortized basis), where n is the size of the me ..."
Abstract

Cited by 6 (2 self)
 Add to MetaCart
We propose several modifications to the binary buddy system for managing dynamic allocation of memory blocks whose sizes are powers of two. The standard buddy system allocates and deallocates blocks in \Theta(lg n) time in the worst case (and on an amortized basis), where n is the size of the memory. We present two schemes that improve the running time to O(1) time, where the time bound for deallocation is amortized. The first scheme uses one word of extra storage compared to the standard buddy system, but may fragment memory more than necessary. The second scheme has essentially the same fragmentation as the standard buddy system, and uses O(2 (1+ p lg n) lg lg n ) bits of auxiliary storage, which is !(lg k n) but o(n " ) for all k 1 and " ? 0. Finally, we present simulation results estimating the effect of the excess fragmentation in the first scheme.
Fast Allocation and Deallocation with an Improved Buddy System
, 2003
"... We propose several modifications to the binary buddy system for managing dynamic allocation of memory blocks whose sizes are powers of two. The standard buddy system allocates and deallocates blocks in Θ(lg n) time in the worst case (and on an amortized basis), where n is the size of the memory. We ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
We propose several modifications to the binary buddy system for managing dynamic allocation of memory blocks whose sizes are powers of two. The standard buddy system allocates and deallocates blocks in Θ(lg n) time in the worst case (and on an amortized basis), where n is the size of the memory. We present three schemes that improve the running time to O(1) time, where the time bound for deallocation is amortized for the first two schemes. The first scheme uses just one more word of memory than the standard buddy system, but may result in greater fragmentation than necessary. The second and third schemes have essentially the same fragmentation as the standard buddy system, and use O(2 (1+ √ lg n) lg lg n) bits of auxiliary storage, which is ω(lg k n) but o(n ε) for all k ≥ 1 and ε> 0. Finally, we present simulation results estimating the effect of the excess fragmentation in the first scheme.
NoBreak Dynamic Defragmentation . . .
, 2008
"... We propose a new method for defragmenting the module layout of a reconfigurable device, enabled by a novel approach for dealing with communication needs between relocated modules and with inhomogeneities found in commonly used FPGAs. Our method is based on dynamic relocation of module positions duri ..."
Abstract
 Add to MetaCart
We propose a new method for defragmenting the module layout of a reconfigurable device, enabled by a novel approach for dealing with communication needs between relocated modules and with inhomogeneities found in commonly used FPGAs. Our method is based on dynamic relocation of module positions during runtime, with only very little reconfiguration overhead; the objective is to maximize the length of contiguous free space that is available for new modules. We describe a number of algorithmic aspects of good defragmentation, and present an optimization method based on tabu search. Experimental results indicate that we can improve the quality of module layout by roughly 50% over static layout. Among other benefits, this improvement avoids unnecessary rejection of modules.