The NVIDIA H100 PCIe, with its 80GB of HBM2e VRAM, offers ample memory to comfortably accommodate the LLaVA 1.6 34B model, which requires approximately 68GB of VRAM when running in FP16 precision. This leaves a 12GB headroom, crucial for managing intermediate calculations and preventing out-of-memory errors during inference. The H100's impressive 2.0 TB/s memory bandwidth ensures rapid data transfer between the GPU and its memory, a critical factor for minimizing latency when processing large language models like LLaVA 1.6 34B.
Furthermore, the H100's Hopper architecture, featuring 14592 CUDA cores and 456 Tensor Cores, is specifically designed to accelerate deep learning workloads. The Tensor Cores are particularly effective at speeding up matrix multiplications, the core operation in transformer-based models like LLaVA 1.6 34B. This combination of high VRAM, exceptional memory bandwidth, and specialized hardware acceleration makes the H100 an excellent choice for running this vision model. The estimated tokens/sec of 78 reflects the performance capability given the large model size and the H100's architecture.
To maximize performance, utilize an optimized inference framework such as vLLM or text-generation-inference, both designed to leverage the H100's capabilities. While FP16 precision is suitable given the available VRAM, consider experimenting with quantization techniques like INT8 or even INT4 to potentially further increase throughput, although this may come with a slight trade-off in accuracy. Monitor GPU utilization and memory usage to ensure optimal resource allocation. Experiment with different batch sizes to find the sweet spot between latency and throughput.
Ensure you have the latest NVIDIA drivers installed to take advantage of the most recent performance optimizations. Profile your application to identify any bottlenecks and fine-tune accordingly. If the performance is not meeting expectations, check that the GPU is not being throttled due to thermal constraints or power limitations, given the H100's 350W TDP.