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  2. Algorithmic efficiency - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_efficiency

    There are up to four aspects of memory usage to consider: The amount of memory needed to hold the code for the algorithm. The amount of memory needed for the input data. The amount of memory needed for any output data. Some algorithms, such as sorting, often rearrange the input data and do not need any additional space for output data.

  3. Java performance - Wikipedia

    en.wikipedia.org/wiki/Java_performance

    Java memory use is much higher than C++'s memory use because: There is an overhead of 8 bytes for each object and 12 bytes for each array [61] in Java. If the size of an object is not a multiple of 8 bytes, it is rounded up to next multiple of 8. This means an object holding one byte field occupies 16 bytes and needs a 4-byte reference.

  4. List of performance analysis tools - Wikipedia

    en.wikipedia.org/wiki/List_of_performance...

    Performance profiler. Shows I/O, communication, floating point operation usage and memory access costs. Supports multi-threaded and multi-process applications - such as those with MPI or OpenMP parallelism and scales to very high node counts. Proprietary CodeAnalyst by AMD: Linux, Windows C, C++, Objective C .NET, Java (works at the executable ...

  5. Green thread - Wikipedia

    en.wikipedia.org/wiki/Green_thread

    It uses green threads to minimize the use of native code, and to support migrating its isolates. Kilim [11] [12] and Quasar [13] [14] are open-source projects which implement green threads on later versions of the JVM by modifying the Java bytecode produced by the Java compiler (Quasar also supports Kotlin and Clojure).

  6. Just-in-time compilation - Wikipedia

    en.wikipedia.org/wiki/Just-in-time_compilation

    The earliest published JIT compiler is generally attributed to work on LISP by John McCarthy in 1960. [4] In his seminal paper Recursive functions of symbolic expressions and their computation by machine, Part I, he mentions functions that are translated during runtime, thereby sparing the need to save the compiler output to punch cards [5] (although this would be more accurately known as a ...

  7. List of tools for static code analysis - Wikipedia

    en.wikipedia.org/wiki/List_of_tools_for_static...

    Java — — Python RPG IV (AS/400) A platform-independent, command-line static source code analyzer. Integrates with PMD and SpotBugs. Sourcetrail (retired) 2021-04 (2021.4.19) Yes; GPL — C, C++ Java — — Python Perl An open-source source code explorer that provides interactive dependency graphs and supports multiple programming languages ...

  8. Manual memory management - Wikipedia

    en.wikipedia.org/wiki/Manual_memory_management

    In computer science, manual memory management refers to the usage of manual instructions by the programmer to identify and deallocate unused objects, or garbage.Up until the mid-1990s, the majority of programming languages used in industry supported manual memory management, though garbage collection has existed since 1959, when it was introduced with Lisp.

  9. Memory footprint - Wikipedia

    en.wikipedia.org/wiki/Memory_footprint

    In a Java program, the memory footprint is predominantly made up of the runtime environment in the form of Java virtual machine (JVM) itself that is loaded indirectly when a Java application launches. In addition, on most operating systems, disk files opened by an application too are read into the application's address space, thereby ...