Cuda工作

More details will be shared via chat with potential freelancer

More details will be shared via chat with potential freelancer

More details will be shared via chat with potential freelancer

More details will be shared via chat

More details will be shared via chat

Using CUDA to accelerate computation on GPU Here you find a small program which is a simplification of a large Simulink-Program. The is ca. 20-times faster than the !! I am beginner in CUDA and I do not make any optimization w.r.t. memory access (shared-memory…).

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We have an application in C/C++ that needs to be recoded to optimized it for GPUs

The project is an AI computational vision , it need to be transferred from CPU pipe line C++ program to GPU parallel programing code , in order to be able to distribute the computational load of multicamera streams such that have min frame rate per second not less than 30 fps. Thus we can determine the limitation of each GPU device towards number of streams within corresponding AI processing features.

...support me with different IT tasks and cooperate with me till the requirements are 100% fulfilled. ( Mobile Application Development, Game Development, Desktop Development, Web Development ) Mobile: Mobile App Development, Android, iPhone PhoneGap, Ionic Framework, Xamarin, react native, flutter, ionic. DESKTOP: Java, Python, C# Programming, C Programming, Socket IO, Linux, C++ Programming, Qt++,CUDA,VB, Blockchain. Web: Core: PHP, HTML, CSS, WordPress, Javascript, HTML, CSS, Angular, node.js, Ruby on Rails, React.js, ASP.NET, React Native, ExpressJS, AJAX, MVC, VB.NET, JSON, Vue.js, RESTful API Blockchain: Metaverse, Web3, NFT, NFT Games, Smart Contract, White Paper, Blockchain (WAX, Solana, BSC, Polygon), Pancake, Arbitrage Bot, Uniswap, DEX, DAPP eCommerce: Woo+BigComm...

We have an application in C/C++ that needs to be recoded to optimized it for GPUs

High Knowledge in MPI, OPEN MP, and CUDA required

This project is to explore feasibility of improving Opus codec performance on CUDA language. with up to 256 channels of streams is encoded/decoded at the same time, the algorithm should be implemented with minimum latency.

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Vehicle number plates should be detected using yolo and using custom trained dataset licence plate should be recognised and based upon certain condition of number plate of india, that has to be stored in database. the system has to be highly accurate. no false results. the system should be trained well as per indian license plates. knowledge of following is must : Python, using nvidia cuda, yolo darknet (or any other), mysql etc No experiments with the time and effort. The same should not be copied from interet open source and built. Efficient and accurate engine is required

I need to rewrite the python source code to use the GPU - CUDA instead of the CPU. I have a Geforce RTX 3070 OC 8GB graphics card. The code must be rewritten so that it uses maximally the performance of the card. Maximum number of threads and maximum speed. You need to add a few more lines to show the current hashrate (MH / s). I was thinking about using Numba libraries Example:

I would like someone who has experience in OpenCV, CUDA, GStreamer and Docker. I would like for someone to build me a docker container that will allow me to stream an RTSP feed in mp4 with bounding boxes over the faces. I am only after facial detection and NOT any facial recognition. I would like the container to be able to accept an RTSP feed using openCV and Nivida GPU CUDA cores to decode and apply bounding boxes on peoples faces, once this is done I need it to stream the video in mp4. Here is a docker container that has most of what we need, just need to add rtsp stream, bounding boxes and out a mp4 stream.

Project title: Anomaly detection using graph neural networks (GNN) I found a project source code on github, and I need someone to teach me on how to run it (and possibly make minor changes to it). Preferably someone with computer science/data science background, but others with experience are welcomed to teach me. project requirements: python, pytorch, CUDA

Làm về sử dụng cuda jit python

I was following the instructions of a python program provided in GitHub, but I am unable to execute the shortcut made at the end of the steps. Github website: The steps are as follows: Download and install Python3. Download and install the latest version of CUDA Toolkit. Download and install Git. Download and unzip the latest Auto Maple release. Download the TensorFlow model and unzip the "models" folder into Auto Maple's "assets" directory. Inside Auto Maple's main directory, open a command prompt and run: python -m pip install -r Lastly, create a desktop shortcut by running: python Deliverables Project scope: help me finish the python program as the developer intended help me understand how to automate Maplestory and solve

I have CUDA installed and having problem installing PyCUDA.

Hello, who can install CUDA Toolkit for Python for me? CUDA 11.7 already installed on my Ubuntu 20 System with some issues Please use Teamviever OR AnyDesk Command Lines tell: >>nvcc --version ..... Cuda compilation tools, release 11.7, V11.7.99 Build cuda_11.7.r11.7/compiler.31442593_0 >>nvidia-smi NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.

Instalar CUDA, Cudnn, PyTorch para proyecto de Python YOLOv5

1) Update existing training script/settings to train on locally stored video files using GPU (CUDA). Use dataset. 2) Script/command to export trained streaming model (trained in the previous step) as quantized TF Lite model 3) Script to test classification of random video from the dataset on TF Lite Streaming model (exported in the previous step) (can use as the starting point) 4) Update "Fine-Tune a Base Model with the TensorFlow Model Garden" example to fine-tune streaming

Necesito instalar y compilar un programa que es público en mi Ubuntu 20.04.

...application to be built, that runs AI based detection on an incoming video stream (4k/hi-res), and generates crop coordinates (y1,x1,y2,x2) for a HD resolution output, in real time (or with as little buffering as possible). The application would also need to apply some smoothing to the output coordinates. We're looking for someone with experience in OpenCV and in particular, using OpenCV CUDA/GPU based coding. This is an application to be run under Ubuntu Linux on a Nvidia Jetson Xavier NX The application will be used on the Nvidia Jetson ecosystem, and needs to utilize the Jetsons GPU and AI processing abilities (as opposed to using CPU based resources). AI model framework can be at the choosing of the developer. We have done some testing around ONNX models ...

Hi it's a pleasure meeting you I'm looking for a machine learning python expert who uses docker version v2.5 or greater regularly so I'm looking for a torch implementation of a graph attention network which will provide intelligence to a financial advisor using good ml statistics on regular st...version v2.5 or greater regularly so I'm looking for a torch implementation of a graph attention network which will provide intelligence to a financial advisor using good ml statistics on regular statistical parameters for stable investment The problem will be broken down into 10 milestones of 40$ each and we will have status updates plus regular code reviews. we'll be using pandas or cudf cupy cuda and neural networks correspondingly. expert in torch, cudf,...

Hi Mirza Muhammad A., I noticed your profile and would like to offer you my project. We can discuss any details over chat.

Attached are a few images that you can use to test. 1. Need the full source code. 2. Should use GPU for processing as the rest of the code uses Cuda 10.1 3. Tesseract can be used if you are confident enough to pre-process the images for the tesseract to recognize. 4. For pre-processing you can use your own code(without plugins) or use EMGUCV(preferred) Note: Normal tesseract 5 is not able to detect these texts correctly (Tried it already)

OMG I just reapaired PC my GPU burned I had to replace it. and after that notebboks stopped to work. I got such problem when running a training tried to follow also But i am getting only pip errors. would you helo me with that I am totally stucked....I need help ASAP I need help via AnyDesk

I would like to get CUDA kernels written for some OpenCV functions that have not already been ported to CUDA. To start: * moments() * warpPolar() There may be a few others in the future.

Hi there, I have a project solution in Visual Studio, using C++ and OpenGL. Is a simulation of some geometric shapes and their movement in space, using gravity, collisions and friction. (This is provided) The project runs entirely on the CPU and I need someone to parallelize whatever can pe parallelized using CUDA or plane Compute Shaders. The project is not big. Send me proposal so I will send further details

I have a project solution in Visual Studio, using C++ and OpenGL. Is a simulation of some geometric shapes and their movement in space, using gravity, collisions and friction. (This is provided) The project runs entirely on the CPU and I need someone to parallelize whatever can pe parallelized using CUDA or plane Compute Shaders. The project is not big. Let me know, if you are interested

Hello I have one remaining function (Quick Sort) in my project still run in CPU I want to move to GPU using CUDA that all.

Hello! I am doing some personal researches in artificial intelligence for fun and for learning. To do so I create (more or less) simple deep learning n...just 30% while the CPU is not the limiting factor. My graphic card is a Geforce 2070. Letting the training process run on a Geforce 3090 the GPU utilization has just 17%. I think that here are also optimization options in preparing the input data, reducing overhead, how to optimal use the VRAM of a Geforce card and especially how to improve the processes between CPU and GPU regarding all options of CUDA and cudnn. May be that OneFlow automatical manage some of that steps by itsself. I don't know. I want to use the service for training so a multi GPU support is also required. If you have any questions, don't hesitate to...

I would like to convert some optimization (second-order non convex optimization) PyTorch code to C++. Ideally the code will also implement a supporting package which is imported and have CUDA support, but willing to fund work where the code uses an alternative optimizer like LBFGS and versions with no GPU parallelization support. Also interested in multiprecision support if possible. Rate negotiable depending on ability to tend to details above.

I would like to convert some optimization (second-order non convex optimization) PyTorch code to C++. Ideally the code will also implement a supporting package which is imported and have CUDA support, but willing to fund work where the code uses an alternative optimizer like LBFGS and versions with no GPU parallelization support. Also interested in multiprecision support if possible. Rate negotiable depending on ability to tend to details above.

Hi Vasilatos. My goal is to improve the performance of some pytorch code in any way I can. If I can get a significant time improvement by switching to C++, I would be interested in having you rewrite it there. I'm willing to pay you to implement it in C++. What would be your rate on this with and without gpu parallelization? (e.g. with and without CUDA support, since I am still interested in cpu timing enhancement)

Hi, i currently have a cuda script which handles some basic sha256 hashing this script works fine on a single thread, however i will need to run this on a multi threaded platform which is where i get an exception if i try to run on more than 1 thread i will provide the .cu script along with a c# testing project so you can replicate the issue this should be a very easy project for someone familiar with .cu code however my code is messy as i am not familiar with it and this being my first time working with it if you think you can do this please let me know

Hi, i currently have a cuda script which handles some basic sha256 hashing this script works fine on a single thread, however i will need to run this on a multi threaded platform which is where i get an exception if i try to run on more than 1 thread i will provide the .cu script along with a c# testing project so you can replicate the issue this should be a very easy project for someone familiar with .cu code however my code is messy as i am not familiar with it and this being my first time working with it if you think you can do this please let me know

Hi, i currently have a cuda script which handles some basic sha256 hashing this script works fine on a single thread, however i will need to run this on a multi threaded platform which is where i get an exception if i try to run on more than 1 thread i will provide the .cu script along with a c# testing project so you can replicate the issue this should be a very easy project for someone familiar with .cu code however my code is messy as i am not familiar with it and this being my first time working with it if you think you can do this please let me know

Implement the "Accessible Population" algorithm. It is mandatory that the implementation be performed on the GPU using CUDA and any implementation that does not comply with this requirement automatically leads to the loss of the entire score on the topic.

I want parallel Bitonic code sort using Cuda by c I have the rules for the code and I want these to be implemented. ( it is a very different way from the codes available on the Internet).

Deliver CUDA Programs that meet the requirements in the attached document. Attachments 1) the Cuda Program Requirements document 2) Cuda code files that need to be modified

can you write a bitonic sort program using Cuda (parallel programming ) ?

write a bitonic sort program using Cuda (parallel programming )

write a bitonic sort program using Cuda (parallel programming )

write a bitonic sort program using Cuda (parallel programming )

write a bitonic sort program using Cuda

Hi Aditya, Do you have experience with CUDA? I am looking to port over a small parallelized optimization procedure from PyTorch to CUDA. I think for someone with experience with these languages this should take a couple hours or less. I'm willing to negotiate on the rate though. Best,