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About

vLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more.

About

The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks. Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications! Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI infrastructure engineers looking for a solution to optimize the deployment and serving of large-scale language models in production environments

Audience

Developers requiring an adaptable and real-time AI inference acceleration solution to build accelerated applications

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

vLLM
United States
vllm.ai

Company Information

Xilinx
Founded: 1984
United States
www.xilinx.com/products/design-tools/vitis/vitis-ai.html

Alternatives

Alternatives

OpenVINO

OpenVINO

Intel

Categories

Categories

Integrations

Allegro X Design Platform
Amazon Web Services (AWS)
Database Mart
Docker
Hugging Face
KServe
Kubernetes
LDRA Tool Suite
ModelSim
NGINX
NVIDIA DRIVE
OpenAI
OrCAD X
Pulsonix
PyTorch
Rapita Verification Suite
TensorFlow
Thunder Compute
ZEDEDA
omp

Integrations

Allegro X Design Platform
Amazon Web Services (AWS)
Database Mart
Docker
Hugging Face
KServe
Kubernetes
LDRA Tool Suite
ModelSim
NGINX
NVIDIA DRIVE
OpenAI
OrCAD X
Pulsonix
PyTorch
Rapita Verification Suite
TensorFlow
Thunder Compute
ZEDEDA
omp
Claim vLLM and update features and information
Claim vLLM and update features and information
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