MicroprocessorA microprocessor is a computer processor where the data processing logic and control is included on a single integrated circuit (IC), or a small number of ICs. The microprocessor contains the arithmetic, logic, and control circuitry required to perform the functions of a computer's central processing unit (CPU). The IC is capable of interpreting and executing program instructions and performing arithmetic operations.
Control-flow graphIn computer science, a control-flow graph (CFG) is a representation, using graph notation, of all paths that might be traversed through a program during its execution. The control-flow graph was discovered by Frances E. Allen, who noted that Reese T. Prosser used boolean connectivity matrices for flow analysis before. The CFG is essential to many compiler optimizations and static-analysis tools. In a control-flow graph each node in the graph represents a basic block, i.e.
Fibonacci heapIn computer science, a Fibonacci heap is a data structure for priority queue operations, consisting of a collection of heap-ordered trees. It has a better amortized running time than many other priority queue data structures including the binary heap and binomial heap. Michael L. Fredman and Robert E. Tarjan developed Fibonacci heaps in 1984 and published them in a scientific journal in 1987. Fibonacci heaps are named after the Fibonacci numbers, which are used in their running time analysis.
Status registerA status register, flag register, or condition code register (CCR) is a collection of status flag bits for a processor. Examples of such registers include FLAGS register in the x86 architecture, flags in the program status word (PSW) register in the IBM System/360 architecture through z/Architecture, and the application program status register (APSR) in the ARM Cortex-A architecture. The status register is a hardware register that contains information about the state of the processor.
Weak heapIn computer science, a weak heap is a data structure for priority queues, combining features of the binary heap and binomial heap. It can be stored in an array as an implicit binary tree like a binary heap, and has the efficiency guarantees of binomial heaps. A sorting algorithm using weak heaps, weak-heapsort, uses a number of comparisons that is close to the theoretical lower bound on the number of comparisons required to sort a list, so is particularly useful when comparison is expensive, such as when comparing strings using the full Unicode collation algorithm.
Memory management unitA memory management unit (MMU), sometimes called paged memory management unit (PMMU), is a computer hardware unit that examines all memory references on the memory bus, translating these requests, known as virtual memory addresses, into physical addresses in main memory. In modern systems, programs generally have addresses that access the theoretical maximum memory of the computer architecture, 32 or 64 bits. The MMU maps the addresses from each program into separate areas in physical memory, which is generally much smaller than the theoretical maximum.
Heap (data structure)In computer science, a heap is a specialized tree-based data structure that satisfies the heap property: In a max heap, for any given node C, if P is a parent node of C, then the key (the value) of P is greater than or equal to the key of C. In a min heap, the key of P is less than or equal to the key of C. The node at the "top" of the heap (with no parents) is called the root node. The heap is one maximally efficient implementation of an abstract data type called a priority queue, and in fact, priority queues are often referred to as "heaps", regardless of how they may be implemented.
Tracing garbage collectionIn computer programming, tracing garbage collection is a form of automatic memory management that consists of determining which objects should be deallocated ("garbage collected") by tracing which objects are reachable by a chain of references from certain "root" objects, and considering the rest as "garbage" and collecting them. Tracing garbage collection is the most common type of garbage collection – so much so that "garbage collection" often refers to tracing garbage collection, rather than other methods such as reference counting – and there are a large number of algorithms used in implementation.
Garbage collection (computer science)In computer science, garbage collection (GC) is a form of automatic memory management. The garbage collector attempts to reclaim memory which was allocated by the program, but is no longer referenced; such memory is called garbage. Garbage collection was invented by American computer scientist John McCarthy around 1959 to simplify manual memory management in Lisp. Garbage collection relieves the programmer from doing manual memory management, where the programmer specifies what objects to de-allocate and return to the memory system and when to do so.
Code generation (compiler)In computing, code generation is part of the process chain of a compiler and converts intermediate representation of source code into a form (e.g., machine code) that can be readily executed by the target system. Sophisticated compilers typically perform multiple passes over various intermediate forms. This multi-stage process is used because many algorithms for code optimization are easier to apply one at a time, or because the input to one optimization relies on the completed processing performed by another optimization.
Just-in-time compilationIn computing, just-in-time (JIT) compilation (also dynamic translation or run-time compilations) is compilation (of computer code) during execution of a program (at run time) rather than before execution. This may consist of source code translation but is more commonly bytecode translation to machine code, which is then executed directly. A system implementing a JIT compiler typically continuously analyses the code being executed and identifies parts of the code where the speedup gained from compilation or recompilation would outweigh the overhead of compiling that code.
D-ary heapThe d-ary heap or d-heap is a priority queue data structure, a generalization of the binary heap in which the nodes have d children instead of 2. Thus, a binary heap is a 2-heap, and a ternary heap is a 3-heap. According to Tarjan and Jensen et al., d-ary heaps were invented by Donald B. Johnson in 1975. This data structure allows decrease priority operations to be performed more quickly than binary heaps, at the expense of slower delete minimum operations.
