From 4b45d2daeb9f574d13ae0e774677c87c04ef2124 Mon Sep 17 00:00:00 2001
From: Misha Chornyi <99709299+mc-nv@users.noreply.github.com>
Date: Mon, 28 Aug 2023 13:01:27 -0700
Subject: [PATCH] Update README for 1.31.0 / 23.08 (#752)
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README.md | 91 +++++++++++++++++++++++++++++++++++++++++++++++++++++--
1 file changed, 88 insertions(+), 3 deletions(-)
diff --git a/README.md b/README.md
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+++ b/README.md
@@ -14,6 +14,91 @@ See the License for the specific language governing permissions and
limitations under the License.
-->
-**Warning**
-You are currently on the r23.08 branch which tracks stabilization towards the next release.
-This branch is not usable during stabilization.
\ No newline at end of file
+[](https://opensource.org/licenses/Apache-2.0)
+
+# Triton Model Analyzer
+
+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
+
+- [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): **EARLY ACCESS** - 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
+
+### 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.
+
+
+# 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.