5x the performance of the H100, but you'll need liquid cooling to tame the beast
Given Nvidia's meteoric rise in the wake of the generative AI boom, the stakes couldn't be higher. But at least on paper, Blackwell — the successor to Nvidia's venerable Hopper generation — doesn't disappoint. In terms of raw FLOPS, the GPU giant's top-specced Blackwell chips are roughly 5x faster.
And it's this silicon which is at least partially responsible for Blackwell's performance gains this generation. Each GPU is actually two reticle-limited compute dies, which are tied together via a 10 TBps NVLink-high-bandwidth-interface fabric , which allows them to function as a single accelerator The two compute dies are flanked by a total of eight HBM3e memory stacks up to 192GB of capacity and 8 TBps of bandwidth.
Where things get interesting is with the B200. In an air cooled HGX or DGX configuration, each GPU can push 18 petaFLOPS of FP4 while sucking down a kilowatt. According to Nvidia its DGX B200 chassis with eight B200 GPUs will consume roughly 14.3kW something that's going to require roughly 60kW of rack power and thermal headroom to handle.
Nvidia's most powerful GPUs can be found in its GB200. Similar to Grace-Hopper, the new Grace-Blackwell Superchip meshes together its existing 72-core Grace CPU with its Blackwell GPUs using its NVLink-C2C interconnect. Compared to last-gen, this dual GB200 system is capable of churning out more FLOPS than its 8U 10.2kW DGX H100 systems — 40 petaFLOPS vs 32 petaFLOPS — while consuming an eighth the space.These dual GB200 systems form the backbone of Nvidia's new NVL72 rack scale AI systems which are designed to support large-scale training and inference deployments on models scaling to trillions of parameters
According to Nvidia, the approach allows a single NVL72 rack system can support model sizes up to 27 trillion parameters — presumably when using FP4. In training, Nvidia says the system is good for 720 petaFLOPS at what we assume is dense FP4 precision. For inferencing workloads, meanwhile, we're told the system will do 1.44 exaFLOPS at FP4. If that's not enough horsepower, eight NVL72 racks can be networked to form Nvidia's DGX BG200 Superpod.
The system's NVLink switches now feature a pair of Nvidia's fifth-gen 7.2 Tbps NVLink ASICs, each of which are capable of 1.8 TBps of all-to-all bidirectional bandwidth — twice that of last gen. As we mentioned earlier, the MI300X is something of a silicon sandwich which uses advanced packaging to vertically stack eight CDNA 3 compute units onto four I/O dies, which provide high speed communications between the GPUs and 192GB of HBM3 memory.In terms of performance, the MI300X promised a 30 percent performance advantage in FP8 floating point calculations and a nearly 2.5x lead in HPC centric double precision workloads compared to Nvidia's H100.
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