The hidden cost of cloud GPU training: egress, idle time, and lock-in
The article discusses the hidden costs associated with cloud GPU training, focusing on idle time, egress fees, and vendor lock-in. It highlights how many users pay for GPU hours that go unused, leading to significant waste. Additionally, it emphasizes the importance of considering data transfer costs and the challenges of moving data between providers.
- ▪Average GPU utilization across major clouds is around 5 percent, leading to wasted costs.
- ▪Egress fees for moving data out of cloud services can significantly increase overall expenses.
- ▪Vendor lock-in becomes a financial burden as accumulated data makes it costly to switch providers.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3956731) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Andrea Susic Posted on May 28 The hidden cost of cloud GPU training: egress, idle time, and lock-in #ai #agents #database The GPU hourly rate is the number everyone compares. It is also the number that tells you the least about what a training run actually costs. The sticker price, say $2 to $3.50 an hour for an H100 on a specialized cloud, is the visible tip.
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