Accelerate large neural network training with distributed parallelism
Colossal-AI is a framework that helps you train massive AI models faster by using distributed computing techniques. It splits the workload across multiple GPUs or servers, reducing training time and resource costs. This makes it ideal for handling state-of-the-art models that would otherwise be too slow or expensive to train.
Scale AI model training across multiple devices for faster results
Combine data and model parallelism to optimize performance and efficiency
Manage projects and launch distributed jobs from the command line
Customize training parameters and hyperparameters for your specific needs
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Recent data shows that Colossal-AI has 8.4K monthly visits (3.4% increase from the previous month), 49.0% bounce rate, and average 1.34 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by United States contributing 57% of total traffic. SEO performance is shown by 5 tracked keywords, with "colossal ai" being the top-performing keyword with 720 monthly searches. See below for more info.
Monthly Visits
8.4K
Pages per Visit
1.34
Bounce Rate
49.0%
Average Time on Site
11s
| SEO Keyword | Volume | CPC |
|---|---|---|
| colossal ai | 720 | - |
| colossalai | 110 | - |
| 1f1b | 130 | - |
| nvme become memory gpu cuda | 150 | - |
| what is tensor parallelism and pipeline parallelism | 450 | - |
| Source | Traffic Share |
|---|---|
| Direct | 52% |
| Search | 32% |
| Social | 7% |
| Referrals | 8% |
| Paid Referrals | 1% |
| Country Name | Traffic Share |
|---|---|
 | 57% |
 | 13% |
 | 10% |
 | 7% |
 | 3% |
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