Hierarchical KV Caching: Scaling Context Beyond VRAM Limits
As context windows scale to a million tokens, the KV cache becomes too large for GPU memory. The solution is a multi-tiered cache that offloads data to CPU and NVMe without killing latency.
Tag: AI Infrastructure
· Rajat Pandit · AI InfrastructurevLLM Continuous Batching & PagedAttention: Maximizing Throughput
vLLM continuous batching combined with PagedAttention dramatically increases inference throughput. Learn how this architecture eliminates KV cache fragmentation and boosts GPU utilization by 3x.