Search Results for "python-dpkt" - Page 2
Sort By:
Showing 571 open source projects for "python-dpkt"
View related business solutions-
Run Any Workload on Compute Engine VMsCompute Engine delivers high-performance virtual machines for web apps, databases, containers, and AI workloads. Choose from general-purpose, compute-optimized, or GPU/TPU-accelerated machine types—or build custom VMs to match your exact specs. With live migration and automatic failover, your workloads stay online. New customers get $300 in free credits.
-
Managed MySQL, PostgreSQL, and SQL Databases on Google CloudCloud SQL is a fully managed relational database for MySQL, PostgreSQL, and SQL Server. We handle patching, backups, replication, encryption, and failover—so you can focus on your app. Migrate from on-prem or other clouds with free Database Migration Service. IDC found customers achieved 246% ROI. New customers get $300 in credits plus a 30-day free trial.
-
1
Fast Binary Encoding (FBE)
Fast Binary Encoding is fast and universal serialization solution
Fast Binary Encoding is ultra fast and universal serialization solution for C++, C#, Go, Java, JavaScript, Kotlin, Python, Ruby, and Swift. Fast Binary Encoding allows to description of any domain models, business objects, complex data structures, client/server requests & responses and generate native code for different programming languages and platforms. -
2
C++ Requests
C++ Requests: Curl for People, a spiritual port of Python Requests
C++ Requests is a simple wrapper around libcurl inspired by the excellent Python Requests project. Despite its name, libcurl’s easy interface is anything but, and making mistakes misusing it is a common source of error and frustration. Using the more expressive language facilities of C++11, this library captures the essence of making network calls into a few concise idioms. If there's no package for your distribution, try making one! -
3
MegEngine
Easy-to-use deep learning framework with 3 key features
...In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference. -
4
Faiss
Library for efficient similarity search and clustering dense vectors
...It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It assumes that the instances are represented as vectors and are identified by an integer, and that the vectors can be compared with L2 (Euclidean) distances or dot products. ... -
Build on Google Cloud with $300 in Free CreditStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query exabytes in BigQuery, or build AI apps with Vertex AI and Gemini. Once your credits are used, keep building with 20+ products with free monthly usage, including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. Sign up to start building right away.
-
5
Open Asset Import Library
The open-asset-importer-library repository
...In the past, it has been used in a wide range of applications. Written in C++, it is available under a liberal BSD license. There is a C API as well as bindings to various other languages, including C#, Python and D. Assimp loads all input model formats into one straightforward data structure for further processing. -
6
Double Conversion
Efficient binary-decimal & decimal-binary conversion routines for IEEE
Double Conversion is a high-performance C++ library that provides precise and efficient binary-decimal and decimal-binary conversion routines for IEEE 754 double-precision floating-point numbers. Originally extracted from the V8 JavaScript engine, it was refactored into a standalone library to make its robust number conversion algorithms easily reusable in other projects. The library ensures consistent and accurate results for converting between double values and their string... -
7
TensorStore
Library for reading and writing large multi-dimensional arrays
...The library is engineered for scalability—background caching, chunk sharding, and retryable operations keep throughput high even over unreliable networks. With language bindings, it fits into Python-heavy analysis pipelines while retaining a fast C++ core. -
8
OpenSpiel
Environments and algorithms for research in general reinforcement
...OpenSpiel also includes tools to analyze learning dynamics and other common evaluation metrics. Games are represented as procedural extensive-form games, with some natural extensions. The core API and games are implemented in C++ and exposed to Python. Algorithms and tools are written both in C++ and Python. To try OpenSpiel in Google Colaboratory, please refer to open_spiel/colabs subdirectory. -
9
F´
A flight software and embedded systems framework
...To develop applications with F´, the following requirements of the user’s system must be met, Linux or Mac OS X operating system (or Windows Subsystem for Linux on Windows), CMake, Bash or Bash compatible shell, Clang or GCC compiler, Python 3 and PIP. F´ can be quickly installed and ready to use by cloning the GitHub repository, installing Python code (typically in a virtual environment), and building one of our reference applications. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
-
10
Protocol Buffers
Google's data interchange format
...It allows you to define how your data should be structured once, and then using a special generated source code, you can then easily write and read your structured data to and from a variety of data streams and using a variety of languages. Protocol Buffers currently supports a wide array of languages, including C++, Java, Python, Ruby, and many others with more to come. -
11
glslViewer
Console-based GLSL Sandbox for 2D/3D shaders shaders
GlslViewer is a flexible console-based OpenGL Sandbox to display 2D/3D GLSL shaders without the need of a UI. You can definitely make your own UI or wrapper using the Python Module (include) or any other tool that communicates back/forth with the GPS viewer through the standard POSIX console In/Out or OSC. Default vert/frag shaders for 2D shader and 3D material shaders with PBR lighting model. Hot reload of files on changes. One default light and one default camera. Interactive commands thought POSIX console IN/OUT or OSC. ... -
12
glbinding
A C++ binding for the OpenGL API, generated using the gl.xml specifica
...It provides type-safe parameters, per-feature API headers, lazy function resolution, multi-context and multi-thread support, global and local function callbacks, meta information about the generated OpenGL binding and the OpenGL runtime, as well as tools and examples for quick-starting your projects. Based on the OpenGL API specification (gl.xml) glbinding is generated using Python scripts and templates that can be easily adapted to fit custom needs. -
13
CasADi
CasADi is a symbolic framework for numeric optimization
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. These expression graphs, encapsulated in Function objects, can be evaluated in a virtual machine or exported to stand-alone C code. Initial value problems in ordinary or differential-algebraic equations (ODE/DAE) can be calculated using explicit or implicit Runge-Kutta methods or interfaces to IDAS/CVODES from the SUNDIALS suite. ... -
14
Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
...Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding. -
15
RenderDoc
RenderDoc is a stand-alone graphics debugging tool
RenderDoc is a free MIT licensed stand-alone graphics debugger that allows quick and easy single-frame capture and detailed introspection of any application using Vulkan, D3D11, OpenGL & OpenGL ES or D3D12 across Windows 7 - 10, Linux, Android, Stadia, or Nintendo Switch™. I work on RenderDoc myself and you can always contact me with any problems or comments. I'll respond to you directly and personally, and I'm used to helping people with private or NDA'd projects. RenderDoc is 100% open... -
16
XLS
XLS: Accelerated HW Synthesis
XLS is an open-source toolkit for building high-level hardware with a modern compiler stack that spans from a functional DSL to optimized IR and hardware generation. At the front end, DSLX lets you describe algorithms with strong typing and familiar control flow while remaining synthesis-friendly. The compiler lowers DSLX into a rich intermediate representation, applies aggressive optimization and scheduling passes, and can either JIT the design for software simulation or emit Verilog for... -
17
ccapi
A header-only C++ library for interacting with crypto exchanges
A header-only C++ library for streaming market data and executing trades directly from cryptocurrency exchanges (i.e. the connections are between your server and the exchange server without anything in-between). -
18
OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous... -
19
DALI
A GPU-accelerated library containing highly optimized building blocks
The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding,... -
20
mlpack
mlpack: a scalable C++ machine learning library
...It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. Written in C++ and built on the Armadillo linear algebra library, the ensmallen numerical optimization library, and parts of Boost. Aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. mlpack uses CMake as a build system and allows several flexible build configuration options. ... -
21
re2
Alternative to backtracking regular expression engines
RE2 is a fast, safe, thread-friendly alternative to backtracking regular expression engines like those used in PCRE, Perl, and Python. It is a C++ library. This is the source code repository for RE2, a regular expression library. There is a fair amount of documentation (including code snippets) in the re2.h header file. Unless otherwise noted, the RE2 source files are distributed under the BSD-style license found in the LICENSE file. In POSIX mode, RE2 accepts standard POSIX (egrep) syntax regular expressions. ... -
22
FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to... -
23
SageMaker TensorFlow
SageMaker specific extensions to TensorFlow
This package contains SageMaker-specific extensions to TensorFlow, including the PipeModeDataset class, that allows SageMaker Pipe Mode channels to be read using TensorFlow Datasets. This package supports Python 3.7-3.9 and TensorFlow versions 1.7 and higher, including 2.0-2.9.1. For TensorFlow 1.x support, see the master branch. sagemaker-tensorflow releases for all supported versions are available on PyPI. SageMaker TensorFlow extensions builds on Python 3.4-3.9 in Linux with a TensorFlow version >= 1.7. Older versions of TensorFlow are not supported. ... -
24
CPU Features
A cross platform C99 library to get cpu features at runtime
cpu_features is a cross-platform C library developed by Google that provides a simple and efficient way to detect available CPU features at runtime across a wide range of architectures and operating systems. It enables applications to determine which instruction sets (such as SSE, AVX, or NEON) are supported on the host machine, allowing developers to optimize performance dynamically. The library supports numerous architectures—including x86, ARM, AArch64, MIPS, POWER, RISCV, LoongArch, and... -
25
PyCXX is a set of classes to help create extensions of Python in the C++ language. The first part encapsulates the Python C API taking care of exceptions and ref counting. The second part supports the building of Python extension modules in C++.
