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Model load with gcs fuse benchmarking tool #863

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111 changes: 111 additions & 0 deletions tools/model-load-benchmark/README.md
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Here’s an expanded README with a section detailing how to install the Go package as a CLI:

---

# Benchmarker CLI

A CLI tool for configuring and running benchmarks on various configurations.
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## Table of Contents
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- [Installation](#installation)
- [From Source](#from-source)
- [As a Go Package](#as-a-go-package)
- [Usage](#usage)
- [Commands](#commands)
- [Examples](#examples)

## Installation

### From Source
1. **Clone the repository**:

2. **Build the CLI tool**:
```bash
go build -o benchmarker
```

3. **Move the executable** (optional):
```bash
mv benchmarker /usr/local/bin/
```
This allows you to use the `benchmarker` command globally.

## Setup
```bash
gcloud container clusters get-credentials
```
Ensure cluster credentials are configured in kubeconfig with gcloud credential helper.
The cluster must be able to scale up nodes or have existing nodes.

## Usage

The Benchmarker CLI provides commands to set configurations and run benchmarks.

### Commands

#### `config`
Manage configurations for benchmarks.

- **Usage**: `benchmarker config [subcommand]`
- **Subcommands**:
- `set`: Set a configuration file for benchmarks.

#### `run`
Run the benchmark with the current configuration.

- **Usage**: `benchmarker run`
- **Description**: Executes the benchmark process based on the specified configuration file.

## Examples

### Have a pod spec for benchmarking
Create a pod spec you want to benchmark data loading time for,
make sure to configure Readiness probes to ensure that data expected is loaded by fuse.
Also add necessary node selectors to ensure benchmarking pods are run on preferred nodes.
[Example pod spec](example-pod.yaml)

### Set a Configuration File
To set a configuration file named `config.yaml`, use:
```bash
benchmarker config set -f config.yaml
```
[Example config](base-config.yaml). Set limits higher than base,
ensure the units are consistent in base and max value. Cases with Bool fields set to false and true are both generated. When file cache is not enabled, other settings are not applied. Some cases may result in failure, due to pod scheduling.



### Run a Benchmark
After setting the configuration, run the benchmark with:
```bash
benchmarker run
```

## Plotting Results

The Benchmarker CLI includes a result visualization feature to help analyze benchmark performance across different configurations. This feature loads YAML result files, extracts key metrics, and generates scatter plots for elapsed time against various configuration parameters.

### Prerequisites
Ensure you have the following Python packages installed:
```bash
pip install -r requirements.txt
```

### Results directory
The YAML result files should be stored in a directory named `results`, with filenames following the format `case_<number>.yaml` (e.g., `case_1.yaml`, `case_2.yaml`).

### Running the Plotting Script

1. **Generate YAML result files** by running your benchmarks and saving the results in the `results` directory.
2. **Run the plotting script** to generate scatter plots:
```bash
python plot_results.py
```

This script will:
**Generate Plots**: Scatter plots showing elapsed time versus each parameter, saved as PNG files in the `results` directory.
Each point on the scatter plots is labeled with the **case number** and its configuration is saved in `case_**case_number**.yaml`

## Example Plots
### Elapsed Time vs Max Parallel Downloads
![Elapsed Time vs Max Parallel Downloads](results/elapsed_time_vs_cpu_request.png)
![Elapsed Time vs Max Parallel Downloads](results/elapsed_time_vs_max_parallel_downloads.png)
62 changes: 62 additions & 0 deletions tools/model-load-benchmark/base-config.yaml
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basePodSpec: "example-pod.yaml"
sideCarResources:
cpu-limit:
base: 20
max: 20
step: 5
memory-limit:
base: 2Gi
max: 2Gi
step: 20
ephemeral-storage-limit:
base: 50Gi
max: 50Gi
step: 20
cpu-request:
base: 200m
max: 250m
step: 50
memory-request:
base: 1Gi
max: 3Gi
step: 2
ephemeral-storage-request:
base: 40Gi
max: 40Gi
step: 10
volumeAttributes:
bucketName: "vertex-model-garden-public-us"
mountOptions:
implicit-dirs: true
only-dir: "codegemma/codegemma-2b"
file-cache:
enable-parallel-downloads: true
parallel-downloads-per-file:
base: 4
step: 5
max: 5
max-parallel-downloads:
base: 2
step: 2
max: 5
download-chunk-size-mb:
base: 3
step: 3
max: 6
fileCacheCapacity:
base: 10Gi
step: 2
max: 10Gi
fileCacheForRangeRead: true
metadataStatCacheCapacity:
base: 500Mi
step: 20
max: 500Mi
metadataTypeCacheCapacity:
base: 500Mi
step: 20
max: 500Mi
metadataCacheTTLSeconds:
base: 600
step: 20
max: 620
2 changes: 2 additions & 0 deletions tools/model-load-benchmark/benchmarker.ini
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[default]
MODEL_LOAD_BENCHMARK_CONFIG = base-config.yaml
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