Search Results for "tpc-c benchmark"
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Showing 325 open source projects for "tpc-c benchmark"
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Benchmark
A microbenchmark support library
A library to benchmark code snippets, similar to unit tests. -
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XMRig
RandomX, KawPow, CryptoNight, AstroBWT and GhostRider unified miner
High performance, open-source, cross-platform RandomX, KawPow, CryptoNight, and AstroBWT CPU/GPU miner, RandomX benchmark, and stratum proxy. XMRig is a high-performance, open-source, cross-platform RandomX, KawPow, CryptoNight, and AstroBWT unified CPU/GPU miner and RandomX benchmark. Official binaries are available for Windows, Linux, macOS, and FreeBSD. The preferred way to configure the miner is the JSON config file as it is more flexible and human-friendly. The command-line interface... -
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Crow Framework
A Fast and Easy to use microframework for the web
...Get started by installing Crow and building you first application. Or go through the guides if you're stuck somewhere. Easy Routing (similar to flask). Type-safe Handlers. Blazingly fast (see this benchmark and this benchmark). Built-in JSON support. Mustache-based templating library (crow::mustache). Header-only library (single header file available). Middleware support for extensions. HTTP/1.1 and Websocket support. Multi-part request and response support. Uses modern C++ (11/14). -
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CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
CodeGeeX is a large-scale multilingual code generation model with 13 billion parameters, trained on 850B tokens across more than 20 programming languages. Developed with MindSpore and later made PyTorch-compatible, it is capable of multilingual code generation, cross-lingual code translation, code completion, summarization, and explanation. It has been benchmarked on HumanEval-X, a multilingual program synthesis benchmark introduced alongside the model, and achieves state-of-the-art... -
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LZ4
Extremely fast compression algorithm
LZ4 is lossless compression algorithm, providing compression speed > 500 MB/s per core (>0.15 Bytes/cycle). It features an extremely fast decoder, with speed in multiple GB/s per core (~1 Byte/cycle). A high compression derivative, called LZ4_HC, is available, trading customizable CPU time for compression ratio. LZ4 library is provided as open-source software using a BSD license. This benchmark simulates simple "static content transfer" scenario such as OS Kernel compression or video game's... -
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plow
A high-performance HTTP benchmarking tool
Plow is an HTTP(S) benchmarking tool, written in Golang. It uses excellent fast HTTP instead of Go's default net/http due to its lightning-fast performance. Plow runs at specified connections (option -c) concurrently and real-time records summary statistics, histogram of execution time and calculates percentiles to display on Web UI and terminal. It can run for a set duration( option -d), for a fixed number of requests(option -n), or until Ctrl-C is interrupted. The implementation of... -
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Likwid
Performance monitoring and benchmarking suite
Likwid is a simple to install and use toolsuite of command line applications and a library for performance oriented programmers. It works for Intel, AMD, ARMv8 and POWER9 processors on the Linux operating system. There is additional support for Nvidia and AMD GPUs. There is support for ARMv7 and POWER8/9 but there is currently no test machine in our hands to test them properly. -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. ... -
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CapFrameX
Frametime capture and analysis tool
CapFrameX is a performance capture and analysis tool designed for PC gamers and benchmarking enthusiasts, which records frametimes, frame-rates and various sensor data during game or application execution. It uses backend tools like PresentMon to log data and then exposes a comprehensive UI for analyzing the results: you can view charts of frametimes, historic graphing, stuttering analysis, L-shape graphs, input-lag overlays, and compare multiple capture runs side by side. Importantly, the... -
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Snappy
A fast compressor/decompressor
Snappy is a compression/decompression library. It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression. For instance, compared to the fastest mode of zlib, Snappy is an order of magnitude faster for most inputs, but the resulting compressed files are anywhere from 20% to 100% bigger. Snappy is intended to be fast. On a single core of a Core i7 processor in 64-bit mode, it compresses at... -
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DifferentialEquations.jl
Multi-language suite for high-performance solvers of equations
...The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research which routinely outperform the “standard” C/Fortran methods, and include algorithms optimized for high-precision and HPC applications. At the same time, it wraps the classic C/Fortran methods, making it easy to switch over to them whenever necessary. ... -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
...We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++) and optimized for highly distributed computing environments. This makes them hardly accessible for students, researchers and hackers. Many simple Python implementations can be found on Github, but none of them is able to beat a reasonable baseline on games such as Othello or Connect Four. As an illustration, the benchmark in the README of the most popular of them only features a random baseline, along with a greedy baseline that does not appear to be significantly stronger. -
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OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE)
...The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research that routinely outperform the “standard” C/Fortran methods, and include algorithms optimized for high-precision and HPC applications. At the same time, it wraps the classic C/Fortran methods, making it easy to switch over to them whenever necessary. ... -
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youki
A container runtime written in Rust
...Here is a simple benchmark of a container from creation to deletion. -
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The Arcade Learning Environment
The Arcade Learning Environment (ALE) -- a platform for AI research
Arcade Learning Environment (ALE) is a widely used open-source framework that wraps hundreds of Atari 2600 games via an emulator and presents them as RL environments for AI agents. It decouples the game/emulation aspects from the agent interface, providing a clean API (C++, Python, Gymnasium) so researchers can focus on agent design rather than game plumbing. This environment suite has been central to many RL breakthroughs, including value-based agents, deep Q-nets, and general-agent... -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
...It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. Configuration is managed via protobuf files to define tasks such as self-play, benchmark agent comparisons, and RL training. The project is now archived and read-only, reflecting that it is no longer actively developed but remains publicly available for research use. -
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benchmarksql3
Databases Benchmark for iBoxDB and SQLite
Databases Benchmark, iboxdb sqlite... Goto SourceCode and Download -
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DeepGEMM
Clean and efficient FP8 GEMM kernels with fine-grained scaling
DeepGEMM is a specialized CUDA library for efficient, high-performance general matrix multiplication (GEMM) operations, with particular focus on low-precision formats such as FP8 (and experimental support for BF16). The library is designed to work cleanly and simply, avoiding overly templated or heavily abstracted code, while still delivering performance that rivals expert-tuned libraries. It supports both standard and “grouped” GEMMs, which is useful for architectures like Mixture of... -
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GoNB
GoNB, a Go Notebook Kernel for Jupyter
Go is a compiled language, but with very fast compilation, that allows one to use it in a REPL (Read-Eval-Print-Loop) fashion, by inserting a "Compile" step in the middle of the loop -- so it's a Read-Compile-Run-Print-Loop — while still feeling very interactive. GoNB leverages that compilation speed to implement a full-featured (at least it's getting there) Jupyter notebook kernel. As a side benefit it works with packages that use CGO — although it won't parse C code in the cells, so it... -
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Skiplist-CPP
A tiny KV storage based on skiplist written in C++ language
Skiplist-CPP is a lightweight key-value storage engine implemented in C++ using a skip list as its core data structure. It showcases how a log-structured, ordered index can deliver fast inserts, lookups, and deletes while remaining simple to implement and reason about. The project supplies a compact codebase with a clear separation between the skip list implementation and the storage operations that use it. -
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nmon for Linux
Linux performance monitoring on-screen or to CSV file
nmon is short for Nigel's Performance Monitor It either shows you the stats on-screen updating once a second or saves the data to a CSV file for later analysis and graphing. For details see the homepage ==> http://nmon.sourceforge.net Please use the latest version. The new version "njmon" outputs JSON format that a lot of tools use these days. It integrates well with saving data directly to InfluxDB and graphing with Grafana. -
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LinuxHardware Info
Hardware Info for Linux portable AppImage + Benchmark
LinuxHardware Info (portable/AppImage) -------------------------------------- Ihr wollt wissen was in Eurem Rechner steckt? Genau das könnt Ihr mit LinuxHardwareInfo, ohne jedes mal die Konsole zu bemühen. Kurz-Info: - Hardware Analyse - einfache Benchmarks (CPU / Grafik/RAM und HHD) - CPU-Live Sensoren - Portable AppImage (einfach vom USB-Stick in Live-Image kopieren) - und anderes - im Support-Forum gibt es alle Infos -
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7-max increases the performance of some applications up to 10-20%. Windows uses small (4 KB) RAM pages by default. 7-max allows to use large (2 MB) RAM pages.
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Prime number ( primenumbers )
Benchmark for 50 000 000 prime numbers as single and multicore
Simple source files and compiled JAR Java programs, for benchmark 50 000 000 cycle finding prime numbers. On Intel(R) Core(TM) i5-8600K CPU, Windows 10 20H2, i have 39 second on single core and 7,6 second on multi core. (PS: C++ multicore 6 second). Added C files for gcc compiler in Windows 10 and for Xcode C command line project in MacOS ( tested on Mac mini M2 with single core 16 to 25 sec and multicore 2,3 to 5 second by compiler -O switch).
