The reference specification calls for a GPU Boost frequency of 1545 MHz and a slightly lower TDP. And because Nvidia cites peak compute performance using GPU Boost numbers, its top-end model achieves up to 14.2 TFLOPS of single-precision math.
Again, at the SM level, we find 64 CUDA cores, eight Tensor cores, one RT core, four texture units, 16 load/store units, 256KB of register file space, four L0 instruction caches, and a 96KB configurable L1 cache/shared memory structure.Īt least on the Founders Edition card, a base core frequency of 1350 MHz jumps all the way up to a typical GPU Boost rate of 1635 MHz, so long as GeForce RTX 2080 Ti is running cool enough. Each TPC is composed of one PolyMorph Engine (fixed-function geometry pipeline) and two Streaming Multiprocessors (SMs).
Turing fp64 upgrade#
They were consequently replaced with Micron-made GDDR6, facilitating a cheaper solution that’s still able to serve up a big bandwidth upgrade over Pascal-based predecessors.Ī complete TU102 processor comprises six Graphics Processing Clusters (GPCs) made up of a Raster Engine and six Texture Processing Clusters (TPCs). Similarly, GV100’s eight 512-bit memory controllers attached to four stacks of HBM2 would have ended up being very expensive (just ask AMD about the trouble it had pricing HBM2-equipped Radeons competitively). As a result, TU102’s double-precision rate is 1/32 of its FP32 performance, leaving just enough FP64 compute to maintain compatibility with software dependent on it.
They aren’t really useful in games though, and they eat up a lot of die space, so Nvidia pulled all but two of them from each Turing SM. For example, each Volta Streaming Multiprocessor (SM) includes 32 FP64 cores for fast double-precision math, adding up to 2688 FP64 cores across GV100.
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