Use LSF blaunch command in LSFJob to start the workers in a multitask job

Hello, I am using Dask with IBM LSF cluster, I noted that the current LSF Cluster implementation does not give the ability to start an LSF job on multiple hosts, which can be achieved by using the LSF `blaunch` command.

### Modification proposal

The current way of starting multiple workers on one job that has multiple tasks (`-n` bsub option) is by setting the `--nworkers` option of `distributed.cli.dask_worker` to the number of tasks. Could it be a better option to use instead the `blaunch` command provided by LSF to run a command on each requested task ? In this way the workers will be dispatched on the different hosts provided by LSF and the `span[hosts=1]` will not be required anymore.

Here a test code I made by subclassing LSFJob class to try using `blaunch`.
```python
class CustomLSFJob(LSFJob):

def __init__(self, scheduler=None, name=None, **kwargs):
super().__init__(scheduler=scheduler, name=name, **kwargs)

self._command_template = (
f"blaunch '/path/to/python -m distributed.cli.dask_worker {self.scheduler} --name {name}-$LSF_PM_TASKID --nthreads 1 --memory-limit 1.86GiB --nworkers 1 --nanny --death-timeout 60'"
)

self.job_header = self.job_header.replace(
'#BSUB -R "span[hosts=1]"',
'#BSUB -R "span[hosts=-1]"',
)

class CustomLSFCluster(LSFCluster):
job_cls = CustomLSFJob
```
This code is not usable as is, but I think the changes will only be limited to the constructor of the `LSFJob` class.

Is this an interesting idea ?