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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

vLLM is an advanced library tailored for the efficient inference and deployment of Large Language Models (LLMs). Initially created at the Sky Computing Lab at UC Berkeley, it has grown into a collaborative initiative enriched by contributions from both academic and industry sectors. The library excels in providing exceptional serving throughput by effectively handling attention key and value memory through its innovative PagedAttention mechanism. It accommodates continuous batching of incoming requests and employs optimized CUDA kernels, integrating technologies like FlashAttention and FlashInfer to significantly improve the speed of model execution. Furthermore, vLLM supports various quantization methods, including GPTQ, AWQ, INT4, INT8, and FP8, and incorporates speculative decoding features. Users enjoy a seamless experience by integrating easily with popular Hugging Face models and benefit from a variety of decoding algorithms, such as parallel sampling and beam search. Additionally, vLLM is designed to be compatible with a wide range of hardware, including NVIDIA GPUs, AMD CPUs and GPUs, and Intel CPUs, ensuring flexibility and accessibility for developers across different platforms. This broad compatibility makes vLLM a versatile choice for those looking to implement LLMs efficiently in diverse environments.

Description

Xilinx's AI development platform for inference on its hardware includes a suite of optimized intellectual property (IP), tools, libraries, models, and example designs, all crafted to maximize efficiency and user-friendliness. This platform unlocks the capabilities of AI acceleration on Xilinx’s FPGAs and ACAPs, accommodating popular frameworks and the latest deep learning models for a wide array of tasks. It features an extensive collection of pre-optimized models that can be readily deployed on Xilinx devices, allowing users to quickly identify the most suitable model and initiate re-training for specific applications. Additionally, it offers a robust open-source quantizer that facilitates the quantization, calibration, and fine-tuning of both pruned and unpruned models. Users can also take advantage of the AI profiler, which performs a detailed layer-by-layer analysis to identify and resolve performance bottlenecks. Furthermore, the AI library provides open-source APIs in high-level C++ and Python, ensuring maximum portability across various environments, from edge devices to the cloud. Lastly, the efficient and scalable IP cores can be tailored to accommodate a diverse range of application requirements, making this platform a versatile solution for developers.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) No 
Database Mart Yes 
Docker Yes 
DocsGPT Yes 
Hugging Face Yes 
KServe Yes 
Kubernetes Yes 
ModelSim No 
Muse Spark Open Yes 
NGINX Yes 
NVIDIA DRIVE Yes 
Nemotron 3.5 Bolt Yes 
Nemotron 3.5 Super VL Yes 
OpenAI Yes 
OrCAD X No 
Pulsonix No 
PyTorch Yes 
TensorFlow No 
ZEDEDA No 
omp Yes 

Integrations

Amazon Web Services (AWS) Yes 
Database Mart No 
Docker No 
DocsGPT No 
Hugging Face No 
KServe No 
Kubernetes No 
ModelSim Yes 
Muse Spark Open No 
NGINX No 
NVIDIA DRIVE No 
Nemotron 3.5 Bolt No 
Nemotron 3.5 Super VL No 
OpenAI No 
OrCAD X Yes 
Pulsonix Yes 
PyTorch No 
TensorFlow Yes 
ZEDEDA Yes 
omp No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

vLLM

Country

United States

Website

vllm.ai

Vendor Details

Company Name

Xilinx

Founded

1984

Country

United States

Website

www.xilinx.com/products/design-tools/vitis/vitis-ai.html

Product Features

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives

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