SimAI Components

        |--- AICB
SimAI --|--- SimCCL
        |--- astra-sim-alibabacloud
        |--- ns-3-alibabacloud

SimAI Overview
- Introduction
- Citation
Usage

SimAI Overview

Introduction

SimAI is the industry's first full-stack, high-precision Simulator for AI large-scale training. It provides detailed modeling and simulation of the entire LLM training process, encompassing framework, collective communication, network layers, and more. This comprehensive approach offers end-to-end performance data, enabling researchers to:

Analyze training process details
Evaluate the time consumption of AI tasks under specific conditions
Evaluate E2E performance gains from various algorithmic optimizations including:
- Framework parameters settings
- Collective communication algorithms
- NCCL environment variables
- Network transmission protocols
- Congestion control algorithms
- Adaptive routing algorithms
- Scale-up/out network topology modifications
- ...

Building on pure simulation capabilities, SimAI has evolved into a versatile full-stack toolkit comprising four components (aicb, SimCCL, astra-sim-alibabacloud, ns-3-alibabacloud). These components can be combined in various ways to achieve different functionalities. Below, we present the six main usage scenarios for SimAI. We encourage users to explore even more possibilities with this powerful tool.

Scenario	Description	Component Combination
1. AICB Test Suite	Run communication patterns on GPU clusters using AICB Test suite	AICB
2. AICB/AIOB Workload	Model compute/communication patterns of training process to generate workload	AICB
3. Collective Comm Analyze	Break down collective communication operations into point-to-point communication sets	SimCCL
4. Collective Comm w/o GPU	Perform RDMA collective communication traffic on non-GPU clusters	AICB + SimCCL + astra-sim-alibabacloud(physical)
5. SimAI-Analytical	Conduct rapid AICB workload analysis and simulation on any server (ignoring underlying network details)	AICB + astra-sim-alibabacloud(analytical)
6. SimAI-Simulation	Perform full simulation on any server	AICB + SimCCL + astra-sim-alibabacloud(simulation) + ns-3-alibabacloud

Below is the architecture diagram of the SimAI Simulator: SimAI_Arc

astra-sim-alibabacloud is extended from astra-sim, we have integrated NCCL algorithms and added some new features.

Citation

SimAI work has been accepted by NSDI'25 Spring, and it'll be showcased soon.

Paper name is "SimAI: Unifying Architecture Design and Performance Tunning for Large-Scale Large Language Model Training with Scalability and Precision" [pdf]() / [slides]() / [video]()

Usage

Here are some simple examples, SimAI full tutorials can be found here: SimAI@Tutorial, aicb@Tutorial, [SimCCL@Tutorial], [ns-3-alibabacloud@Tutorial]

Setup

You can follow the instrucitons below to quickly set up the environtments and run SimAI

From Source Code

The following code has been successfully tested on GCC/G++ 9.4.0, python 3.8.10 in Ubuntu 20.04

# Clone the repository
$ git clone https://github.com/aliyun/SimAI.git
$ cd ./SimAI/

# Clone submodules
$ git submodule update --init --recursive
# Make sure use the newest commit
$ git submodule update --remote

# Compile SimAI-Analytical
$ ./scripts/build.sh -c analytical

# Compile SimAI-Simulation (ns3)
$ ./scripts/build.sh -c ns3

Use SimAI-Analytical

$  ./bin/SimAI_analytical -w example/workload_analytical.txt -g 1024 -g_p_s 8 -r results/test- -busbw example/busbw.yaml

Use SimAI-Simulation

# Create network topo
$ python3 ./astra-sim-alibabacloud/inputs/topo/gen_HPN_7.0_topo_mulgpus_one_link.py -g 128 -gt A100 -bw 400Gbps -nvbw 2400Gbps

# Running
$ AS_SEND_LAT=3 AS_NVLS_ENABLE=1 ./bin/SimAI_simulator -t 16 -w ./example/microAllReduce.txt -n ./HPN_7_0_128_gpus_8_in_one_server_with_400Gbps_A100

aliyun / SimAI

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