# SwitchML

**Repository Path**: aiwep/SwitchML

## Basic Information

- **Project Name**: SwitchML
- **Description**: https://github.com/microsoft/SwitchML
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-09-04
- **Last Updated**: 2026-09-04

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

Switch-Based Training Acceleration for Machine Learning (SwitchML)
==================================================================

This is an implementation of SwitchML in P4_16, with support for large packets and RDMA via RoCE.

Status
------

This is a work in progress.

Features:
* 256 byte (64 entry) or 1024 byte (256 entry) packets
* Up to 4 8-bit exponents per message
* Up to 32 workers in a job

Limitations:
* Only the first pipeline's front-panel ports (dev_ports 0 through 63) are currently supported, in order to support 1024 byte packets
* When used with RDMA, ICRC checking on the NIC must be disabled. See README.md in RDMAExampleClient for more info.
* The tests are not fully functional right now.

Requirements
------------

The p4 code requires SDE 9.1.0 or above.

For the control plane, Python 2.7 with Scapy and other SDE dependences
is required. This should be installed on any machine/switch with the SDE
installed. 

For use with RDMA, additional dependencies are required. See RDMAExampleClient/README.md for more details.

Instructions
------------

* Clone the switchml repo.
* Build the P4 code with a command like ```p4_build.sh p4/switchml.p4``` or the equivalent.
* Run the control plane with a command like ```python py/switchml.py```.
  * Set the switch MAC and IP with the ```--switch_mac``` and ```--switch_ip``` arguments.
  * To specify ports and MAC addresses, either edit ```py/switchml.py``` or make a version ```py/prometheus-fib.yml``` and load using the ```--ports``` argument.
* For RDMA, job configuration is done via GRPC.
* For SwitchML-UDP, job configuration can be done by loading a file like ```py/prometheus-fib.yml``` with the ```--job``` argument or the ```worker_file``` command in the CLI.

For use with Daiet, ensure Daiet is configured with ```num_updates = 64``` or ```num_updates = 256```.

For use with the RDMA example client, follow the directions in README.md in RDMAExampleClient.

Testing
-------

* Build with SWITCHML_TEST set to minimize register size for speedier
  model initialization:
  ```p4_build.sh p4/switchml.p4 -DSWITCHML_TEST=1```
* After starting model and switchd, run tests with ```bash run_tests.sh```

Glossary
--------

*Pool*: a collection of aggregator slots

*Slot*: register storage for one packet's worth of data

*Set*: each pool element is divided into two sets: odd and even. Pool sizes should always be multiples of two, so that we have storage for both sets.

*Consume*: adding values into registers

*Harvest*: reading aggregated values out of registers


SwitchML packet formats
-----------------------

This code supports two packet formats: the original UDP format, and RoCE v2.

For SwitchML-UDP, the packet is laid out like this:
* Ethernet
* IP
* UDP (base port 0xbee0)
* SwitchML header
* SwitchML exponent header
* SwitchML significands (either 256 bytes or 1024 bytes
* Ethernet FCS

For SwitchML-RDMA, the packet layout is slightly different depending on which part of a message a packet contains. A message with a single packet looks like this:
* Ethernet
* IP
* UDP (dest port: RoCEv2 (4791))
* IB BTH
* IB RETH, with the following components:
  * Address: virtual address response should be directed to
  * rkey: 
    * bits 31:16: currently unused
    * bits 15:1: pool index
    * bit 0: set bit
* IB IMM: contains 4 8-bit exponents
* Payload: significands, either 256 bytes or 1024 bytes
* IB ICRC: ignored
* Ethernet FCS


Design overview
---------------

TBD


Contributing
------------

This project welcomes contributions and suggestions.  Most contributions require you to agree to a
Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us
the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide
a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions
provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.