Search Results for "state-thread"
Sort By:
Showing 38 open source projects for "state-thread"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
-
1
CUTLASS
CUDA Templates for Linear Algebra Subroutines
...It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN. CUTLASS decomposes these "moving parts" into reusable, modular software components abstracted by C++ template classes. These thread-wide, warp-wide, block-wide, and device-wide primitives can be specialized and tuned via custom tiling sizes, data types, and other algorithmic policy. The resulting flexibility simplifies their use as building blocks within custom kernels and applications. To support a wide variety of applications, CUTLASS provides extensive support for mixed-precision computations, providing specialized data-movement and multiply-accumulate abstractions for half-precision floating point (FP16), BFloat16 (BF16), Tensor Float 32 (TF32), etc. -
2
CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
...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 performance compared to other open models like InCoder and CodeGen. CodeGeeX also powers IDE plugins for VS Code and JetBrains, offering features like code completion, translation, debugging, and annotation. The model supports Ascend 910 and NVIDIA GPUs, with optimizations like quantization and FasterTransformer acceleration for faster inference. -
3
InterpretML
Fit interpretable models. Explain blackbox machine learning
In the beginning, machines learned in darkness, and data scientists struggled in the void to explain them. InterpretML is an open-source package that incorporates state-of-the-art machine-learning interpretability techniques under one roof. With this package, you can train interpretable glass box models and explain black box systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. -
4
tt-metal
TT-NN operator library, and TT-Metalium low level kernel programming
...The project is designed for developers who need direct access to the company’s Tensix processor architecture, exposing a programming model that is closer to hardware control than high-level inference frameworks. Instead of following a traditional GPU model centered on massive thread parallelism, the platform is built around a grid of specialized compute nodes called Tensix cores, each with local SRAM, dedicated compute units, and multiple RISC-V control processors. The SDK provides the abstractions and APIs needed to manage data movement, compute kernels, memory coordination, and execution flow across this architecture. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle... -
6
Pedalboard
A Python library for audio
pedalboard is a Python library for working with audio: reading, writing, rendering, adding effects, and more. It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. Internally at Spotify, pedalboard... -
7
rwkv.cpp
INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model
...RWKV is a novel large language model architecture, with the largest model in the family having 14B parameters. In contrast to Transformer with O(n^2) attention, RWKV requires only state from the previous step to calculate logits. This makes RWKV very CPU-friendly on large context lengths. -
8
PaddleSpeech
Easy-to-use Speech Toolkit including Self-Supervised Learning model
PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks in speech and audio, with state-of-art and influential models. Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing modules, and deployment process. Low barriers to install, CLI, Server, and Streaming Server is available to quick-start your journey. -
9
Vowpal Wabbit
Machine learning system which pushes the frontier of machine learning
...There is a specific focus on reinforcement learning with several contextual bandit algorithms implemented and the online nature lending to the problem well. Vowpal Wabbit is a destination for implementing and maturing state-of-the-art algorithms with performance in mind. The input format for the learning algorithm is substantially more flexible than might be expected. Examples can have features consisting of free-form text, which is interpreted in a bag-of-words way. There can even be multiple sets of free-form text in different namespaces. Similar to the few other online algorithm implementations out there. ... -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
10
Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to experiment with new algorithms, as well as for practitioners who want robust, production-ready ASR pipelines. ... -
11
Fastbot-Android Open Source Handbook
Testing tool for modeling GUI transitions
Fastbot_Android (Fastbot 2.0) is a model-based automated testing tool by ByteDance designed to discover stability or usability issues in Android apps by modeling GUI transitions rather than relying purely on random interactions. It blends machine learning and reinforcement-learning approaches to build a transition graph of UI states and use that model to intelligently explore possible user interactions — aiming to replicate more human-like usage patterns and uncover hidden bugs, crashes, or... -
12
Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
-
13
Burn To The Brim
Utility for efficiently grouping files and folders together
...By recursively scanning your designated folders, BTTB matches item sizes to your media capacity, finding a near-perfect selection in milliseconds and an absolute perfect packing configuration in just a few seconds. Burn to the Brim 4.0.0 introduces state-of-the-art machine learning semantic coherence logic to BTTB's classical packing algorithms. -
14
WaveFunctionCollapse
Bitmap & tilemap generation from a single example
This program generates bitmaps that are locally similar to the input bitmap. WFC initializes output bitmap in a completely unobserved state, where each pixel value is in superposition of colors of the input bitmap (so if the input was black & white then the unobserved states are shown in different shades of grey). The coefficients in these superpositions are real numbers, not complex numbers, so it doesn't do the actual quantum mechanics, but it was inspired by QM. Then the program goes into the observation-propagation cycle. ... -
15
YOLO ROS
YOLO ROS: Real-Time Object Detection for ROS
This is a ROS package developed for object detection in camera images. You only look once (YOLO) is a state-of-the-art, real-time object detection system. In the following ROS package, you are able to use YOLO (V3) on GPU and CPU. The pre-trained model of the convolutional neural network is able to detect pre-trained classes including the data set from VOC and COCO, or you can also create a network with your own detection objects. The YOLO packages have been tested under ROS Noetic and Ubuntu 20.04. ... -
16
Virtual Laboratory Environment
A multi-modeling and simulation environment to study complex systems
...The models can be developed with the DEVS formalism or with the classical mathematical formalism: Ordinary Differential Equation with Euler, Range-Kutta or QSS integrator, Finite state automaton (FDDEVS, UML State chart, Hybrid Petri net). The VLE environment provides an IDE to develop C++ models, DEVS coupled models. VLE have also three ports to use the VFL with Python, Java and R programming languages. -
17
Detect and Track
Code release for "Detect to Track and Track to Detect", ICCV 2017
...Built upon a modified version of R-FCN, the code provides implementations using backbone networks such as ResNet-50, ResNet-101, ResNeXt-101, and Inception-v4, with results demonstrating state-of-the-art accuracy on the ImageNet VID dataset. The repository includes MATLAB-based training and testing scripts, along with pre-trained models and pre-computed region proposals for reproducibility. Multiple testing configurations are available, including multi-frame input and enhanced versions that refine tracking boxes and integrate detection confidence across frames. -
18
Caffe Framework
Caffe, a fast open framework for deep learning
...In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. -
19
Caffe
A fast open framework for deep learning
...Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and a great community of contributors that continue to make Caffe state-of-the-art in both code and models. It’s been used in numerous projects, from startup prototypes and academic research projects, to large scale industrial applications. -
20
SmartRoom
Smart services for assistance to conferences, meetings, lectures
...Some services are common - outcome is shown to everyone in the room; some services are personal - accessed individually via mobile end-user devices. The project is done by FRUCT Lab at the IT-park of Petrozavodsk State University (PetrSU), Russia. -
21
LightPCC
Parallel pairwise correlation computation on Intel Xeon Phi clusters
The first parallel and distributed library for pairwise correlation/dependence computation on Intel Xeon Phi clusters. This library is written in C++ template classes and achieves high speed by exploring the SIMD-instruction-level and thread-level parallelism within Xeon Phis as well as accelerator-level parallelism among multiple Xeon Phis. To facilitate balanced workload distribution, we have proposed a general framework for symmetric all-pairs computation by building provable bijective functions between job identifier and coordinate space for the first time. -
22
Distant Speech Recognition
Beamforming and Speech Recognition Toolkit
BTK contains C++ and Python libraries that implement speech processing and microphone array techniques such as speech feature extraction, speech enhancement, speaker tracking, beamforming, dereverberation and echo cancellation algorithms. The Millennium ASR provides C++ and python libraries for automatic speech recognition. The Millennium ASR implements a weighted finite state transducer (WFST) decoder, training and adaptation methods. These toolkits are meant for facilitating research and development of automatic distant speech recognition. -
23
Phrasal
Statistical phrase-based machine translation system
Stanford Phrasal is a state-of-the-art statistical phrase-based machine translation system, written in Java. At its core, it provides much the same functionality as the core of Moses. Distinctive features include: providing an easy to use API for implementing new decoding model features, the ability to translating using phrases that include gaps (Galley et al. 2010), and conditional extraction of phrase-tables and lexical reordering models. -
24
LightSpMV
lightweight GPU-based sparse matrix-vector multiplication (SpMV)
LightSpMV is a novel CUDA-compatible sparse matrix-vector multiplication (SpMv) algorithm using the standard compressed sparse row (CSR) storage format. We have evaluated LightSpMV using various sparse matrices and further compared it to the CSR-based SpMV subprograms in the state-of-the-art CUSP and cuSPARSE. Performance evaluation reveals that on a single Tesla K40c GPU, LightSpMV is superior to both CUSP and cuSPARSE, with a speedup of up to 2.60 and 2.63 over CUSP, and up to 1.93 and 1.79 over cuSPARSE for single and double precision, respectively. -
25
Aquila
Software Architecture for Cognitive Robotics
Aquila 2.0, an open-source cross-platform software architecture for cognitive robotics that makes use of independent heterogeneous CPU-GPU modules with loosely coupled dynamically generated graphical user interfaces.
