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LoopVectorization.jl is a Julia package for accelerating numerical loops by automatically applying SIMD (Single Instruction, Multiple Data) vectorization and other low-level optimizations. It analyzes loops and generates highly efficient code that leverages CPU vector instructions, making it ideal for performance-critical computing in fields such as scientific computing, signal processing, and machine learning.
TimerOutputs.jl is a lightweight Julia package that provides a structured way to measure and report the execution time of different parts of code. It is particularly useful for performance profiling in scientific computing, allowing developers to annotate sections of code and generate readable timing summaries. TimerOutputs.jl supports nested timers and formatted output to both terminal and files, helping users easily identify bottlenecks in their programs.
Project continued at github, see https://github.com/wolfc01/procexp/blob/master/README.md
Graphical process explorer for Linux. Shows process information: process tree, TCP IP connections and graphical performance figures for processes. Aims to mimic Windows procexp from sysinternals, and aims to be more usable than top and ps, especially for advanced users.
Audience for this tool:
* Advanced system administrators trying to analyze on process level what is going on in a production...
The alio library can be dynamically pre-linked to existing executables and replaces file IO (i.e. calls to glibc's IO functions). This allows to gather statistics about IO, create IO trace files, or even implement a different IO behaviour (e.g. use separate IO servers to handle IO).
...No language libraries were used to avoid implementation differences. Some of the benchmarks are also implemented in Python and Scala.
There are benchmarks for bit twiddling, numerical computing, data structure manipulation, concurrent computing, callouts to native libraries, and,
graphics processing units (GPU) utilization.