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; higher-level 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.

We show that for 8 real and varied C and C++ programs, several conventional dynamic storage allocators provide nearzero fragmentation, once we account for overheads due to implementation details such as headers, alignment, etc. This substantially strengthens our previous results showing that the memory fragmentation problem has generally been misunderstood, and that good allocator policies can provide good memory usage for most programs. The new results indicate that for most programs, excellent allocator policies are readily available, and efficiency of implementation is the major challenge. While we believe that our experimental results are state-of-the-art and our methodology is superior to most previous work, more work should be done to identify and study unusual problematic program behaviors not represented in our sample. 1

Garbage collection is the automatic reclamation of computer storage [Knu73, Coh81, Wil92, Wil95]. While in many systems, programmers must explicitly reclaim heap memory at some point in their program by using a "free" or "dispose" statement, garbage collected systems free the programmer from this burden. In spite of its obvious attractiveness for many applications, garbage collection for real-time programs is not popular. This is largely due to the perceived cost and disruptiveness of garbage collection in general, and of incremental garbage collection in particular. Most existing "real-time" garbage collectors are not in fact usefully real-time, largely due to the use of a read barrier to trigger incremental copying of data structures being traversed by the running application. This may slow down running applications unpredictably, even though individual increments of garbage collection work are small and bounded. We have developed a hard real-time garbage collector which us...

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.

. 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. 1 Introduction The binary buddy system [13] is a well-known system for maintaining a dynamic collection of me...

This paper presents a hardware-efficient memory allocation (EMA) technique designed to eliminate both internal and external fragmentation that appear in the buddy system. EMA can allocate a free memory block of any size in any part of memory. Hardware implementation of EMA is introduced, but only part of its circuits is shown in the paper due to the space limitation. Simulation results show that EMA utilizes memory space more efficiently than the previously known techniques.

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.