6-GPU K80 Multiplexer: 0.3ms Model Hot-Swaps

🔑 Enhanced Key Takeaways

• •NVIDIA Tesla K80 features two GK210 GPUs with 4992 CUDA cores total and compute capability 3.7, limiting support to CUDA 11.8 and earlier[2][5][6].
• •Each K80 GPU provides 12GB GDDR5 memory at 480 GB/s aggregate bandwidth, enabling the 72GB total across six dies[1][2][3].
• •K80 offers strong double-precision performance up to 2.91 TFLOPS per card with GPU Boost, advantageous for certain scientific workloads[1][2][4].
• •Recent repurposing efforts highlight K80 viability for offline ML on older CUDA versions, avoiding Tensor Core dependencies[6][8].

🛠️ Technical Deep Dive

• •K80 dual-GPU board uses two GK210 dies, each with 2496 CUDA cores, 12GB GDDR5, and Kepler architecture (compute capability 3.7)[2][5].
• •Supports CUDA up to version 11.8; CUDA 12+ drops Kepler support, requiring compatible LLM frameworks without Tensor Cores[6].
• •Features GPU Boost for dynamic clock scaling, double shared memory/register file vs predecessors, and 480 GB/s memory bandwidth[1][3][4].
• •Both GPUs on K80 can be utilized simultaneously in frameworks like MATLAB for parallel computing[7].

🔮 Future ImplicationsAI analysis grounded in cited sources

⏳ Timeline