NeTS:Small: Efficient Collective Communication for Distributed ML in the Cloud — NSF Award to Cornell University (NY, $525,000)
Machine learning (ML) has transformed how we solve complex problems, from understanding languages to making accurate predictions in medicine and economics. However, modern ML models have grown extremely large—often involving trillions of parameters—that they can no longer run efficiently on a single computer. Instead,
| Award title | NeTS:Small: Efficient Collective Communication for Distributed ML in the Cloud |
|---|---|
| Award ID | 2435852 |
| Awardee | Cornell University |
| City | ITHACA |
| State | NY |
| Amount obligated | $525,000 |
| Principal investigator | Rachee Singh |
| Program | Networking Technology and Syst |
| Start date | 07/15/2025 |
| Abstract | Machine learning (ML) has transformed how we solve complex problems, from understanding languages to making accurate predictions in medicine and economics. However, modern ML models have grown extremely large—often involving trillions of parameters—that they can no longer run efficiently on a single computer. Instead, these enormous models must be distributed across many powerful processors, known as accelerators, in data centers. A critical challenge in running distributed ML models efficiently |
| Source | NSF Awards |
$799/mo
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