I'm somewhat struggling to figure out what SwiftStack does that is special.
It does seem to be a software(?) abstraction layer for massive and varied storage systems?
Is/Are their key advantages scalability? Flexability? Performance across distant supercomputing clusters/centers?
What is their advantage in Nvidia's portfolio? Is Nvidia doing this as a defensive maneuver, like Mellanox? Is there some sort of special IP involved? Is the real aquisition the talent?
Is this a ramp up for GTC news releases and investor call? Is the aquisition cost (not disclosed? not finished?) small enough to not warrent regulator approval?
Are their offices close enough to merge, or are we looking at an Icera-like situation, where the other team is still largely doing their own thing?
From what I can tell, they have two products, one named Storage which is an on-prem object storage program, sort of like MinIO, which lets you also access it as an NTFS/SMB store.
Their second product is 1space, and seems to be a multi-cloud object storage, in that data can be stored in many different places but accessed centrally. I can't see why anyone would need to use this though.
Storage companies get acquired for no reason all the time, probably because they fail and can get picked up cheap.
The diagram that shows Swiftstack used for ML training data looks delusional. If you are tagging images, for instance, you will probably put the images in an object store. The tags are really small in comparison and are a better fit for a database, particularly if you want to spool some subset of them to the trainer in a hurry.
They own the IP for a couple of file storage systems and file formats that improve throughput speeds related to AI specific tasks that assist in reducing training time on images in particular, but could be expanded on with the right research.
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jeremyshaw - Tuesday, March 10, 2020 - link
I'm somewhat struggling to figure out what SwiftStack does that is special.It does seem to be a software(?) abstraction layer for massive and varied storage systems?
Is/Are their key advantages scalability? Flexability? Performance across distant supercomputing clusters/centers?
What is their advantage in Nvidia's portfolio? Is Nvidia doing this as a defensive maneuver, like Mellanox? Is there some sort of special IP involved? Is the real aquisition the talent?
Is this a ramp up for GTC news releases and investor call? Is the aquisition cost (not disclosed? not finished?) small enough to not warrent regulator approval?
Are their offices close enough to merge, or are we looking at an Icera-like situation, where the other team is still largely doing their own thing?
olafgarten - Tuesday, March 10, 2020 - link
From what I can tell, they have two products, one named Storage which is an on-prem object storage program, sort of like MinIO, which lets you also access it as an NTFS/SMB store.Their second product is 1space, and seems to be a multi-cloud object storage, in that data can be stored in many different places but accessed centrally. I can't see why anyone would need to use this though.
PaulHoule - Sunday, March 15, 2020 - link
Storage companies get acquired for no reason all the time, probably because they fail and can get picked up cheap.The diagram that shows Swiftstack used for ML training data looks delusional. If you are tagging images, for instance, you will probably put the images in an object store. The tags are really small in comparison and are a better fit for a database, particularly if you want to spool some subset of them to the trainer in a hurry.
Lakados - Monday, March 16, 2020 - link
They own the IP for a couple of file storage systems and file formats that improve throughput speeds related to AI specific tasks that assist in reducing training time on images in particular, but could be expanded on with the right research.spaces - Monday, March 16, 2020 - link
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