Fast LLM Serving with vLLM and PagedAttention

Anyscale

Fast LLM Serving with vLLM and PagedAttention

1 year ago - 32:07

How to Efficiently Serve an LLM?

Ahmed Tremo

How to Efficiently Serve an LLM?

11 months ago - 12:13

vLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Woosuk Kwon & Xiaoxuan Liu, UC Berkeley

PyTorch

vLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Woosuk Kwon & Xiaoxuan Liu, UC Berkeley

9 months ago - 23:33

What Production-Grade LLM Serving Actually Requires (Infrastructure Deep Dive)

Predibase

What Production-Grade LLM Serving Actually Requires (Infrastructure Deep Dive)

2 months ago - 5:58

E15 | MuxServe: Flexible Multiplexing for Efficient Multiple LLM Serving (ICML'24) 【中文】

MLSys Singapore

E15 | MuxServe: Flexible Multiplexing for Efficient Multiple LLM Serving (ICML'24) 【中文】

1 year ago - 35:14

Simon Mo on vLLM: Easy, Fast, and Cost-Effective LLM Serving for Everyone

AMD Developer Central

Simon Mo on vLLM: Easy, Fast, and Cost-Effective LLM Serving for Everyone

3 weeks ago - 18:08

Scalable and Efficient LLM Serving With the VLLM Production Stack - Junchen Jiang & Yue Zhu

The Linux Foundation

Scalable and Efficient LLM Serving With the VLLM Production Stack - Junchen Jiang & Yue Zhu

3 weeks ago - 39:36

Create your multi-node LLM serving K8s cluster with one click

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Create your multi-node LLM serving K8s cluster with one click

4 months ago - 0:31

Introducing Lemonade Server: Local LLM Serving with GPU and NPU Acceleration

AMD Developer Central

Introducing Lemonade Server: Local LLM Serving with GPU and NPU Acceleration

12 days ago - 6:55

Simplify Your Open-Source LLM Serving with Anyscale's Aviary: Ray Serve Automation & Autoscaling

AI Insight News

Simplify Your Open-Source LLM Serving with Anyscale's Aviary: Ray Serve Automation & Autoscaling

2 years ago - 0:53

[MLArchSys 2025]| Runtime Attestation for Secure LLM Serving in Cloud-Native TEE

Jianchang Su

[MLArchSys 2025]| Runtime Attestation for Secure LLM Serving in Cloud-Native TEE

1 month ago - 8:26

What is vLLM? Efficient AI Inference for Large Language Models

IBM Technology

What is vLLM? Efficient AI Inference for Large Language Models

2 months ago - 4:58

MobiSys 25 Teaser - EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices

ACMMobiSys

MobiSys 25 Teaser - EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices

3 weeks ago - 1:31

Introduction to LLM serving with SGLang - Philip Kiely and Yineng Zhang, Baseten

AI Engineer

Introduction to LLM serving with SGLang - Philip Kiely and Yineng Zhang, Baseten

12 hours ago - 43:42

[MLArchSys 2025]|SafeKV: Safe KV-Cache Sharing in LLM Serving

kexin.chu2017

[MLArchSys 2025]|SafeKV: Safe KV-Cache Sharing in LLM Serving

1 month ago - 11:27

LLM Serving: The 4 Hard Truths No One Tells You

InfoQ

LLM Serving: The 4 Hard Truths No One Tells You

3 weeks ago - 49:59

Lightning Talk: Best Practices for LLM Serving with DRA - Chen Wang & Abhishek Malvankar, IBM

CNCF [Cloud Native Computing Foundation]

Lightning Talk: Best Practices for LLM Serving with DRA - Chen Wang & Abhishek Malvankar, IBM

1 year ago - 9:37

Enabling Cost-Efficient LLM Serving with Ray Serve

Anyscale

Enabling Cost-Efficient LLM Serving with Ray Serve

1 year ago - 30:28

vLLM vs NanoVLLM ⚡ Fast LLM Inference Battle! Which AI Engine Wins?

Serverwala Cloud Data Centers Pvt Ltd

vLLM vs NanoVLLM ⚡ Fast LLM Inference Battle! Which AI Engine Wins?

4 weeks ago - 1:00

LLM Serving (Rust) demo

Fuhai Gao

LLM Serving (Rust) demo

8 months ago - 5:06

MLSys'25 - LServe: Efficient Long-sequence LLM Serving with Unified Sparse Attention

MIT HAN Lab

MLSys'25 - LServe: Efficient Long-sequence LLM Serving with Unified Sparse Attention

2 months ago - 11:36

Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inf. on Heterogen. Syst.

HotCarbon

Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inf. on Heterogen. Syst.

1 year ago - 10:47

Reducing Prefill Delay for LLM Serving in RAG By Sharing Knowledge

Junchen Jiang

Reducing Prefill Delay for LLM Serving in RAG By Sharing Knowledge

1 year ago - 19:10

Efficient LLM Serving on Hybrid Real-time and Best-effort Requests

The Prompt Index

Efficient LLM Serving on Hybrid Real-time and Best-effort Requests

3 months ago - 3:02

Ray Aviary: Open-Source Multi-LLM Serving

John Snow Labs

Ray Aviary: Open-Source Multi-LLM Serving

1 year ago - 19:16

vLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Kaichao You, Tsinghua University

PyTorch

vLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Kaichao You, Tsinghua University

12 days ago - 15:05

MLSys'25 - QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving

MIT HAN Lab

MLSys'25 - QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving

2 months ago - 13:45

Legion Retreat 2024 - Low-Latency, High-Performance LLM Serving and Fine-tuning - Zhihao Jia

Legion Programming System

Legion Retreat 2024 - Low-Latency, High-Performance LLM Serving and Fine-tuning - Zhihao Jia

7 months ago - 30:35

Introducing Ray Aviary | 🦜🔍 Open Source Multi-LLM Serving

Anyscale

Introducing Ray Aviary | 🦜🔍 Open Source Multi-LLM Serving

2 years ago - 13:33

PagedAttention: Revolutionizing LLM Inference with Efficient Memory Management - DevConf.CZ 2025

DevConf

PagedAttention: Revolutionizing LLM Inference with Efficient Memory Management - DevConf.CZ 2025

1 month ago - 28:05

TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices

Keyur

TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices

9 months ago - 8:46

E07 | Fast LLM Serving with vLLM and PagedAttention

MLSys Singapore

E07 | Fast LLM Serving with vLLM and PagedAttention

1 year ago - 55:36

Mélange - Cost Efficient LLM Serving by Using Mixture of GPUs - Hands on Demo

Fahd Mirza

Mélange - Cost Efficient LLM Serving by Using Mixture of GPUs - Hands on Demo

1 year ago - 10:58

GOSIM CHINA 2024-Kaichao You vLLM: Easy, Fast, and Cheap LLM Serving for Everyone

GOSIM Foundation

GOSIM CHINA 2024-Kaichao You vLLM: Easy, Fast, and Cheap LLM Serving for Everyone

8 months ago - 31:42

OSDI '24 - dLoRA: Dynamically Orchestrating Requests and Adapters for LoRA LLM Serving

USENIX

OSDI '24 - dLoRA: Dynamically Orchestrating Requests and Adapters for LoRA LLM Serving

10 months ago - 14:34

GOSIM CHINA 2024 - Kaichao You: vLLM - Easy, Fast, and Cheap LLM Serving for Everyone

GOSIM Foundation

GOSIM CHINA 2024 - Kaichao You: vLLM - Easy, Fast, and Cheap LLM Serving for Everyone

8 months ago - 30:12

SGLang: An Efficient Open-Source Framework for Large-Scale LLM Serving - Liangsheng Yin

PyTorch

SGLang: An Efficient Open-Source Framework for Large-Scale LLM Serving - Liangsheng Yin

12 days ago - 19:37

Building a Multi-Cluster Privately Hosted LLM Serving Platform on Ku... Julian Bright & Noah Yoshida

CNCF [Cloud Native Computing Foundation]

Building a Multi-Cluster Privately Hosted LLM Serving Platform on Ku... Julian Bright & Noah Yoshida

1 year ago - 25:48

vLLM Inference Engine [ಕನ್ನಡದಲ್ಲಿ] | Easy, Fast, and Cheap LLM Serving with PagedAttention

Charan H U

vLLM Inference Engine [ಕನ್ನಡದಲ್ಲಿ] | Easy, Fast, and Cheap LLM Serving with PagedAttention

1 year ago - 15:45

제8회 데보션(DEVOCEAN) 테크 데이 - 06. 리벨리온의 LLM Serving Stack

DEVOCEAN

제8회 데보션(DEVOCEAN) 테크 데이 - 06. 리벨리온의 LLM Serving Stack

3 days ago - 26:23

Unlock LLM Speed: VLLM Crushes the Competition!

Red Hat AI

Unlock LLM Speed: VLLM Crushes the Competition!

1 month ago - 0:48

vLLM: Fast & Affordable LLM Serving with PagedAttention | UC Berkeley's Open-Source Library

AI Insight News

vLLM: Fast & Affordable LLM Serving with PagedAttention | UC Berkeley's Open-Source Library

2 years ago - 2:25

NDSS 2025 - I Know What You Asked: Prompt Leakage via KV-Cache Sharing in Multi-Tenant LLM Serving

NDSS Symposium

NDSS 2025 - I Know What You Asked: Prompt Leakage via KV-Cache Sharing in Multi-Tenant LLM Serving

2 months ago - 16:22

【GOSIM AI Paris 2025】Erwan Gallen & Eldar Kurtic: vLLM: Multi-Accelerator & Quantized LLM Serving

GOSIM Foundation

【GOSIM AI Paris 2025】Erwan Gallen & Eldar Kurtic: vLLM: Multi-Accelerator & Quantized LLM Serving

1 month ago - 21:08

InstCache - A Predictive Cache for LLM Serving

Fahd Mirza

InstCache - A Predictive Cache for LLM Serving

6 months ago - 7:08

R&B song about AnyScale's Aviary, LLM serving library (AI music video) - Sway Ducky

Sway Ducky

R&B song about AnyScale's Aviary, LLM serving library (AI music video) - Sway Ducky

1 year ago - 0:55

LitServe - LLM Serving Inference Engine - Install and Test Locally

Fahd Mirza

LitServe - LLM Serving Inference Engine - Install and Test Locally

10 months ago - 10:29

What is vLLM & How do I Serve Llama 3.1 With It?

Mosleh

What is vLLM & How do I Serve Llama 3.1 With It?

11 months ago - 7:23

LLM inference optimization: Architecture, KV cache and Flash attention

YanAITalk

LLM inference optimization: Architecture, KV cache and Flash attention

10 months ago - 44:06

DistServe: disaggregating prefill and decoding for goodput-optimized LLM inference

PyTorch

DistServe: disaggregating prefill and decoding for goodput-optimized LLM inference

Streamed 9 months ago - 32:03

MLSys Singapore

MLSys Singapore

MLSys Seminar @SG is a special interest group for Machine Learning System researchers and engineers in Singapore. We meet ...

@MLSysSingapore subscribers

Large Language Model Serving - ML Systems Design Interview

TRYEXCEPT

Large Language Model Serving - ML Systems Design Interview

4 months ago - 12:59

#431 LLM ServingとClaude Code - 2025/7/22のZennトレンド

zenncast

#431 LLM ServingとClaude Code - 2025/7/22のZennトレンド

4 days ago - 7:02

vLLM: Easy, Fast, and Cheap LLM Serving, Woosuk Kwon, UC Berkeley

AMD Developer Central

vLLM: Easy, Fast, and Cheap LLM Serving, Woosuk Kwon, UC Berkeley

7 months ago - 22:30

Andes: Defining and Enhancing Quality-of-Experience in LLM-Based Text Streaming Services

UCFCompArch

Andes: Defining and Enhancing Quality-of-Experience in LLM-Based Text Streaming Services

4 months ago - 46:59

[vLLM Office Hours #27] Intro to llm-d for Distributed LLM Inference

Neural Magic

[vLLM Office Hours #27] Intro to llm-d for Distributed LLM Inference

1 month ago - 1:19:57

LMCache Team

LMCache Team

@LMCacheTeam subscribers

Mastering LLM Inference Optimization From Theory to Cost Effective Deployment: Mark Moyou

AI Engineer

Mastering LLM Inference Optimization From Theory to Cost Effective Deployment: Mark Moyou

6 months ago - 33:39

How LLM Use Large Context Windows

Fahd Mirza

How LLM Use Large Context Windows

1 year ago - 3:33

[short] Infinite-LLM: Efficient LLM Service for Long Context with Attention and Distributed KVCache

Arxiv Papers

[short] Infinite-LLM: Efficient LLM Service for Long Context with Attention and Distributed KVCache

1 year ago - 2:59

ACMMobiSys

ACMMobiSys

@ACMMobiSys subscribers

Scaling LLM Inference Globally: Novita AI & Vultr in Partnership

Vultr

Scaling LLM Inference Globally: Novita AI & Vultr in Partnership

4 weeks ago - 13:44

MIT HAN Lab

MIT HAN Lab

MIT HAN Lab: Hardware, AI and Neural-nets Accelerate Deep Learning Computing Group website: hanlab.mit.edu TinyML ...

@MITHANLab subscribers

Serve a Custom LLM for Over 100 Customers

Trelis Research

Serve a Custom LLM for Over 100 Customers

1 year ago - 51:56

kexin.chu2017

kexin.chu2017

@kexin.chu2017 subscribers

Engineering Techniques to Reduce Cost of LLMs in Production [webinar]

TensorOps

Engineering Techniques to Reduce Cost of LLMs in Production [webinar]

1 year ago - 56:48

Predibase

Predibase

The highest quality models with the fastest throughput tailored to your use case—served in your cloud or ours. As the first platform ...

@Predibase subscribers

FAST '25 - Mooncake: Trading More Storage for Less Computation — A KVCache-centric Architecture...

USENIX

FAST '25 - Mooncake: Trading More Storage for Less Computation — A KVCache-centric Architecture...

3 months ago - 17:17

Task Scheduling for Decentralized LLM Serving | Dr. Sanjaya Kumar Panda | GenLang 5.0

S.P.I.T. Media

Task Scheduling for Decentralized LLM Serving | Dr. Sanjaya Kumar Panda | GenLang 5.0

Streamed 2 weeks ago - 4:06:11

Jianchang Su

Jianchang Su

@JianchangSu-cc2fi subscribers

Fuhai Gao

Fuhai Gao

@fuhaigao1117 subscribers

Optimize LLM inference with vLLM

Red Hat

Optimize LLM inference with vLLM

4 days ago - 6:13

PyTorch

PyTorch

Welcome to the official PyTorch YouTube Channel. Learn about the latest PyTorch tutorials, new, and more. PyTorch is an open ...

@PyTorch subscribers

Advancing efficient ML

Google Research

Advancing efficient ML

1 year ago - 12:04