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Vegeta is an HTTP load testing tool written in Go that can be used as a command in a command-line interface or as a library. [4] The program tests how an HTTP-based application behaves when multiple users access it at the same time [4] by generating a background load of GET requests. [5]
For a pair of types K, V, the type map[K]V is the type mapping type-K keys to type-V values, though Go Programming Language specification does not give any performance guarantees or implementation requirements for map types. Hash tables are built into the language, with special syntax and built-in functions.
A pointer a pointing to the memory address associated with a variable b, i.e., a contains the memory address 1008 of the variable b.In this diagram, the computing architecture uses the same address space and data primitive for both pointers and non-pointers; this need should not be the case.
[1] [4] Conversely, the memory order is called weak or relaxed when one thread cannot predict the order of operations arising from another thread. [1] [4] Many naïvely written parallel algorithms fail when compiled or executed with a weak memory order. [5] [6] The problem is most often solved by inserting memory barrier instructions into the ...
In computer science, a memory map is a structure of data (which usually resides in memory itself) that indicates how memory is laid out. The term "memory map" has different meanings in different contexts. It is the fastest and most flexible cache organization that uses an associative memory. The associative memory stores both the address and ...
For this figure, m = 18 and k = 3. An empty Bloom filter is a bit array of m bits, all set to 0. It is equipped with k different hash functions, which map set elements to one of the m possible array positions. To be optimal, the hash functions should be uniformly distributed and independent.
Traditionally, low-memory-footprint programs were of importance to running applications on embedded systems where memory would often be a constrained resource [1] – so much so that developers typically sacrificed efficiency (processing speeds) just to make program footprints small enough to fit into the available RAM.
Region-based memory management works best when the number of regions is relatively small and each contains many objects; programs that contain many sparse regions will exhibit internal fragmentation, leading to wasted memory and a time overhead for region management. Again, in the presence of region inference this problem can be more difficult ...