Search Results for "ai coding model"
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Showing 14 open source projects for "ai coding model"
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers,... -
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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... -
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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... -
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QP Real-Time Event Frameworks & Tools
Real-Time Event Frameworks based on active objects & state machines
QP real-time event frameworks (RTEFs) provide lightweight, modern, event-driven architecture based on asynchronous Active Objects (Actors) and Hierarchical State Machines. The matching QM model-based design tool and other host-based tools complement the QP frameworks by supporting graphical modeling, code generation, software tracing, and unit testing for event-driven embedded software. Visit https://www.state-machine.com for more information. The QP RTEFs can run on bare-metal... -
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. -
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Modern C++ Template
A template for modern C++ projects using CMake, Clang-Format
...Modern CMake configuration and project, which, to the best of my knowledge, uses the best practices. An example of a Clang-Format config, inspired from the base Google model, with minor tweaks. This is aimed only as a starting point, as coding style is a subjective matter, everyone is free to either delete it (for the LLVM default) or supply their own alternative. Static analyzers integration, with Clang-Tidy and Cppcheck, the former being the default option. Doxygen support, through the ENABLE_DOXYGEN option, which you can enable if you wish to use it. ... -
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TNN
Uniform deep learning inference framework for mobile
...On the mobile phone, TNN has been used by many applications such as mobile QQ, weishi, and Pitu. As a basic acceleration framework for Tencent Cloud AI, TNN has provided acceleration support for the implementation of many businesses. Everyone is welcome to participate in the collaborative construction to promote the further improvement of the TNN inference framework. -
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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. ... -
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Model driven code generation can improve coding standards, speed, quality of development and reduce your costs. From my experience generating code from XML using XSLT is one of the best and fastest solutions. This is just the base of the framework presenting the idea, any code template can be implemented upon request. Some sample generators are present for SQL / PLSQL / C# / AnsiC / Java The main target is to generate DTO/BDO/POJO objects based on the database definitions in multiple languages aligning all technologies used by a development team. ...
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AI-powered SAST and AppSec platform that helps companies find and fix vulnerabilities.ZeroPath (YC S24) is an AI-native application security platform that delivers comprehensive code protection beyond traditional SAST. Founded by security engineers from Tesla and Google, ZeroPath combines large language models with advanced program analysis to find and automatically fix vulnerabilities.
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Ash C++ Template Library (AshTL)
Hashing and spatial concurrency library.
AshTL aims to provide a complete framework for dealing with spatial data in an efficient, parallel manner. As such, we primarily provide container classes and data types relating to 2D and 3D coordinate grids. AshTL is currently in alpha development (some features may not work correctly, and interfaces are likely to change). While in alpha and beta development, AshTL is licensed under AGPL v3+. Stable releases will include an exception so that AshTL itself will always be AGPL, but will... -
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PlexBench is a cross-platform, web-enabled, analysis tool that is driven by a scalable backpropagation feed-forward neural network. It uses embedded Perl for scripting and is written in the style of an in-process Component Object Model (COM) C++ program.
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MeMo (stands for Meta-Model) is planned as Generic Programming Language & IDE, as flexible & smart as it is possible for computer application, including adjustable syntax, algorithm reduction. Ideally, it has to contain AI for interacting with the user.
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Plansim is a C++ framework aimed to the development of efficient planner agents based on heuristic forward search, that use discrete event simulators as the model for the agent's environment.
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Framework for modelling of Natural General Intelligence. This project aims at creation of open source AGI (Artificial General Intelligence) through modelling of natural thinking. See http://roland.pri.ee/bakalaureusetoo/ for theoretical details.
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