GPU Support and JavaScript
Table of Contents
Introduction
We present here a quick introduction to GPU support with JavaScript.
There are a couple of updates regarding finding nodes with GPU, querying node for GPU information and deploying with support of GPU.
This is an ongoing development and this section will be updated as new information comes in.
Example
Here is an example script to deploy with GPU support:
import { DiskModel, FilterOptions, MachineModel, MachinesModel, NetworkModel } from "../src";
import { config, getClient } from "./client_loader";
import { log } from "./utils";
async function main() {
const grid3 = await getClient();
// create network Object
const n = new NetworkModel();
n.name = "vmgpuNetwork";
n.ip_range = "10.249.0.0/16";
// create disk Object
const disk = new DiskModel();
disk.name = "vmgpuDisk";
disk.size = 100;
disk.mountpoint = "/testdisk";
const vmQueryOptions: FilterOptions = {
cru: 8,
mru: 16, // GB
sru: 100,
availableFor: grid3.twinId,
hasGPU: true,
rentedBy: grid3.twinId,
};
// create vm node Object
const vm = new MachineModel();
vm.name = "vmgpu";
vm.node_id = +(await grid3.capacity.filterNodes(vmQueryOptions))[0].nodeId; // TODO: allow random choice
vm.disks = [disk];
vm.public_ip = false;
vm.planetary = true;
vm.cpu = 8;
vm.memory = 1024 * 16;
vm.rootfs_size = 0;
vm.flist = "https://hub.grid.tf/tf-official-vms/ubuntu-22.04.flist";
vm.entrypoint = "/";
vm.env = {
SSH_KEY: config.ssh_key,
};
vm.gpu = ["0000:0e:00.0/1002/744c"]; // gpu card's id, you can check the available gpu from the dashboard
// create VMs Object
const vms = new MachinesModel();
vms.name = "vmgpu";
vms.network = n;
vms.machines = [vm];
vms.metadata = "";
vms.description = "test deploying VM with GPU via ts grid3 client";
// deploy vms
const res = await grid3.machines.deploy(vms);
log(res);
// get the deployment
const l = await grid3.machines.getObj(vms.name);
log(l);
// delete
const d = await grid3.machines.delete({ name: vms.name });
log(d);
await grid3.disconnect();
}
main();