From 436fb3105165fe15eed7303e790a7438dfccb3d6 Mon Sep 17 00:00:00 2001 From: Misha Chornyi Date: Fri, 7 Jun 2024 18:31:44 -0700 Subject: [PATCH] Update README file --- README.md | 102 +----------------------------------------------------- 1 file changed, 1 insertion(+), 101 deletions(-) diff --git a/README.md b/README.md index 29d9a07e9..86f6b436b 100644 --- a/README.md +++ b/README.md @@ -22,104 +22,4 @@ limitations under the License. > > ##### LATEST RELEASE > -> You are currently on the `main` branch which tracks under-development progress towards the next release.
-> The latest release of the Triton Model Analyzer is 1.40.0 and is available on branch -> [r24.05](https://github.com/triton-inference-server/model_analyzer/tree/r24.05). - -Triton Model Analyzer is a CLI tool which can help you find a more optimal configuration, on a given piece of hardware, for single, multiple, ensemble, or BLS models running on a [Triton Inference Server](https://github.com/triton-inference-server/server/). Model Analyzer will also generate reports to help you better understand the trade-offs of the different configurations along with their compute and memory requirements. -

- -# Features - -### Search Modes - -- [Optuna Search](docs/config_search.md#optuna-search-mode) **_-ALPHA RELEASE-_** allows you to search for every parameter that can be specified in the model configuration, using a hyperparameter optimization framework. Please see the [Optuna](https://optuna.org/) website if you are interested in specific details on how the algorithm functions. - -- [Quick Search](docs/config_search.md#quick-search-mode) will **sparsely** search the [Max Batch Size](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#maximum-batch-size), - [Dynamic Batching](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#dynamic-batcher), and - [Instance Group](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#instance-groups) spaces by utilizing a heuristic hill-climbing algorithm to help you quickly find a more optimal configuration - -- [Automatic Brute Search](docs/config_search.md#automatic-brute-search) will **exhaustively** search the - [Max Batch Size](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#maximum-batch-size), - [Dynamic Batching](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#dynamic-batcher), and - [Instance Group](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#instance-groups) - parameters of your model configuration - -- [Manual Brute Search](docs/config_search.md#manual-brute-search) allows you to create manual sweeps for every parameter that can be specified in the model configuration - -### Model Types - -- [Ensemble Model Search](docs/config_search.md#ensemble-model-search): Model Analyzer can help you find the optimal - settings when profiling an ensemble model, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm - -- [BLS Model Search](docs/config_search.md#bls-model-search): Model Analyzer can help you find the optimal - settings when profiling a BLS model, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm - -- [Multi-Model Search](docs/config_search.md#multi-model-search-mode): Model Analyzer can help you - find the optimal settings when profiling multiple concurrent models, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm - -- [LLM Search](docs/config_search.md#llm-search-mode): Model Analyzer can help you - find the optimal settings when profiling large language models, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm - -### Other Features - -- [Detailed and summary reports](docs/report.md): Model Analyzer is able to generate - summarized and detailed reports that can help you better understand the trade-offs - between different model configurations that can be used for your model. - -- [QoS Constraints](docs/config.md#constraint): Constraints can help you - filter out the Model Analyzer results based on your QoS requirements. For - example, you can specify a latency budget to filter out model configurations - that do not satisfy the specified latency threshold. -

- -# Examples and Tutorials - -### **Single Model** - -See the [Single Model Quick Start](docs/quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on a simple PyTorch model. - -### **Multi Model** - -See the [Multi-model Quick Start](docs/mm_quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on two models running concurrently on the same GPU. - -### **Ensemble Model** - -See the [Ensemble Model Quick Start](docs/ensemble_quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on a simple Ensemble model. - -### **BLS Model** - -See the [BLS Model Quick Start](docs/bls_quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on a simple BLS model. -

- -# Documentation - -- [Installation](docs/install.md) -- [Model Analyzer CLI](docs/cli.md) -- [Launch Modes](docs/launch_modes.md) -- [Configuring Model Analyzer](docs/config.md) -- [Model Analyzer Metrics](docs/metrics.md) -- [Model Config Search](docs/config_search.md) -- [Checkpointing](docs/checkpoints.md) -- [Model Analyzer Reports](docs/report.md) -- [Deployment with Kubernetes](docs/kubernetes_deploy.md) -

- -# Reporting problems, asking questions - -We appreciate any feedback, questions or bug reporting regarding this -project. When help with code is needed, follow the process outlined in -the Stack Overflow (https://stackoverflow.com/help/mcve) -document. Ensure posted examples are: - -- minimal – use as little code as possible that still produces the - same problem - -- complete – provide all parts needed to reproduce the problem. Check - if you can strip external dependency and still show the problem. The - less time we spend on reproducing problems the more time we have to - fix it - -- verifiable – test the code you're about to provide to make sure it - reproduces the problem. Remove all other problems that are not - related to your request/question. +> You are currently on the `r24.06` branch which tracks under-development progress towards the next release.