31–40 of 114 posts
I feel that the old SETI@home project can use a comeback. Most home machines have powerful GPU these days. The ML problems are embarrassingly parallel and can be distributed to the home machines. Just need to work out the economy for everyone involved.
In my experience, if you want _the_ best price-performance ratio for ML jobs, your best bet is CoreWeave. They have great GPU availability and it's a lot easier to scale up/down very quickly than on the popular clouds. I would really be surprised if anyone else out there is offering a better price point for these types of workloads..
checkout lambda labs, they have very competitive pricing on GPU, they are almost half the price of CoreWeave at the last check.
I wonder why UC Berkeley doesn't build a proper HPC, they have a Data School and should provide this service for free to their faculties. We have "free" HPC resources at TU Dresden (Germany) (meaning: faculties do not need to pay for using HPC resources and they are not calculated in project budgets). I once applied for a job at University of Virginia, and they didn't have a HPC - everything was bought from AWS. When…
From reading this launch post, I'm not convinced this is going to save too much money. The project automatically selects the cheapest cloud to run a job, and does it there - which sounds sensible. In reality though, these jobs presumably need large volumes of input data. If your input data is in cloud A, and you run a job in cloud B, typically any cost saving from running in cloud B will be more than offset by the eg…
SkyPilot is not just for multi clouds. It's useful for all of these scenarios:
- using a single region of one cloud
- using multiple regions of one cloud
- using multiple clouds
Data transfer between zones/regions within a cloud is much cheaper than across clouds. We see many users falling in the "one cloud" category and they frequently read 10s of TBs of data across regions to do ML training.
Finally, saving money is one of several key problems we aim to solve, and there are quite a few ways to save other than lots-of-compute-on-small-data. Other reasons why you may want to use a system like SkyPilot include
(1) improving resource availability (big pain point for GPUs/TPUs)
(2) use one interface and know that your jobs can migrate across regions or clouds
More rationale in the intro blog post: https://medium.com/@zongheng_yang/skypilot-ml-and-data-scien...
Earlier quoted context omitted.
checkout lambda labs, they have very competitive pricing on GPU, they are almost half the price of CoreWeave at the last check.
Lambdalabs is fantastic, but they are so fantastic and popular they often seem to run out of gpus available to rent for me :D
It's fascinating to see the descendants of the original AMP Lab ( https://amplab.cs.berkeley.edu/ ) are still generating value long after it ended. For reference, Spark and Mesos are two other projects that came out of the same effort. This blog post from the authors https://medium.com/@zongheng_yang/skypilot-ml-and-data-scien... I believe autostop (simply stopping idle clusters) alone can masively (X times) costs fo…
I wonder why UC Berkeley doesn't build a proper HPC, they have a Data School and should provide this service for free to their faculties. We have "free" HPC resources at TU Dresden (Germany) (meaning: faculties do not need to pay for using HPC resources and they are not calculated in project budgets). I once applied for a job at University of Virginia, and they didn't have a HPC - everything was bought from AWS. When…
A lot of Berkeley researchers use the NERSC facilities at the nearby Berkeley National Lab: https://www.nersc.gov/
I wonder why UC Berkeley doesn't build a proper HPC, they have a Data School and should provide this service for free to their faculties. We have "free" HPC resources at TU Dresden (Germany) (meaning: faculties do not need to pay for using HPC resources and they are not calculated in project budgets). I once applied for a job at University of Virginia, and they didn't have a HPC - everything was bought from AWS. When…
I think you'd have a hard time finding a better cloud launcher anywhere. I couldn't.
Quite a coincidence :)