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An allocation mechanism designed to optimize the management of large objects by separating them from small ones.
Large objects, typically objects one or more orders of magnitude larger than the virtual memory page of a platform, can be costly to allocate, initialize, and recycle. By segregating those objects into a separate area, they can be managed using specific mechanisms that would be inefficient for smaller objects but which can reduce the cost of manipulating large ones.
Some example mechanisms:
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Also known as
atomic object.
A leaf object is an object that does not reference any other objects.
In a typed language, the compiler can often determine at compile time that certain types can be represented as leaf objects. Usually these types are either a scalar data type or a vector data type of scalars with bounded magnitude.
Relevance to memory management
If leaf objects can be identified, a garbage collector can make certain optimizations: leaf objects do not have to be scanned for references nor are barrier(1) needed to detect and maintain references in the object.
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Also known as
extent, life.
The lifetime or extent of an object is the time for which the object is live.
See also
The allocation policy that always uses the most-recently freed(1) suitable free block. Commonly implemented by pushing freed blocks on the front of a free block chain, and then using first fit allocation on this chain. free(1) can be very quick, depending on the coalescing policy.
This policy may suffer from severe fragmentation in the presence of short-lived large objects of a single size. As smaller objects are allocated, the free block chain fills up with fragments a little smaller than the large object size.
See also
Also known as
sticky reference count.
A reference counting technique whereby the field used to store the number of references to an object has a limited size. In particular, the field is not large enough to represent the maximum possible number of references to an object.
Using the observation that most objects are not referenced a great number of times, some systems that use reference counts only store the count accurately up to a certain maximum value. If an object has more references than the maximum then the count “sticks” at the maximum and is never decremented. Such objects are expected to be rare, but their memory(1) can never be reclaimed using reference counting. A separate (infrequently run) tracing garbage collector is often employed to reclaim this storage.
A degenerate form of limited-field reference counting is one-bit reference counting where an object is considered to be referenced either exactly once or many times.
In linear addressing, addresses form a single, continuous address space. This term is used mostly in opposition to segmented addressing.
Opposite term
Also known as
alive, active.
Memory(2) or an object is live if the program will read from it in future. The term is often used more broadly to mean reachable.
It is not possible, in general, for garbage collectors to determine exactly which objects are still live. Instead, they use some approximation to detect objects that are provably dead, such as those that are not reachable.
Similar term
Opposite term
dead.
See also
To transfer data from memory(2) to a processor’s registers.
Load can also be used in the more general sense of moving data from a part of the memory hierarchy that is slow to access to one that is fast to access (For example, “it takes about 3 ms for the virtual memory system to load a page from disk on this system”). When used in this sense, the qualified term cache(2) load is common.
LOAD (or an abbreviation) is also commonly used in many processor architectures as the mnemonic name for the machine code instructions that are used primarily to make data accessible to the CPU (by loading the data into registers usually). In RISC architectures it is common for the load instructions to be the only means of making data accessible to the CPU; in CISC architectures it is common for a wide variety of instructions to implicitly or explicitly load data from memory.
Opposite term
Locality of reference is the extent to which successive accesses of nearby memory(1) locations are nearby in time; for example, a program that reads all the elements of a contiguous array in turn or that repeatedly uses the same memory variable has good locality of reference.
Good locality of reference interacts well with virtual memory and memory caches, as it reduces the working set and improves the hit rate.
There are a number of specialized senses of locality of reference in certain fields such as distributed systems; these are not covered in depth here.
Relevance to memory management
A mutator may exhibit predictable properties such as accessing in turn objects which were allocated in turn, or accessing in turn objects which have references to each other. An intelligent allocator or copying garbage collector can use this observation to improve locality of reference.
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In the MPS
A location dependency records the fact that the client program depends on the bit patterns of some references (and not merely on the identity of the block to which the reference refers), and provides a function (mps_ld_isstale()) to find out whether any of these references have been changed because a block has been moved. See Location dependency.
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