![]() ![]() But in the case of the TITAN V, we speak about the performance of the tensor cores in deep learning applications. The TITAN V shows an impressive power processing: 110 TFLOPS especially if you put this number in relation with the TFLOPS of a basic GTX 1080: 8.9 TFLOPS. The Volta GV100 GPU packs 5120 CUDA cores and 21 billion transistors! NVIDIA has unveiled the TITAN V: a new graphics card based on the new Volta GV100 GPU architecture (announced in May 2017). Note: Moor Insights & Strategy writers or interns may have contributed to this article.The TITAN-V is built around the Volta GV100-400-A1 GPU ( source). I do not hold any equity positions with any companies cited in this column. Hewlett Packard Enterprise, Huawei Technologies, IBM, Jabil Circuit, Intel, Interdigital, Konica Minolta, Lenovo, Linux Foundation, Mesosphere, Microsoft, National Instruments, NOKIA, Nortek, NVIDIA, ONUG, OpenStack Foundation, Peraso, Pure Storage, Qualcomm, Rackspace, Rambus, Red Hat, Samsung Technologies, Silver Peak, SONY, Springpath, Sprint, Stratus Technologies, Synaptics, Vidyo, Xilinx, Zebra, which may be cited in this article. Some in the media will weigh in on TITAN V in gaming workloads, but that’s completely missing the point.ĭisclosure: My firm, Moor Insights & Strategy, like all research and analyst firms, provides or has provided research, analysis, advising, and/or consulting to many high-tech companies in the industry, including Advanced Micro Devices, Applied Micro, Apstra, ARM Holdings, Bitfusion, Cisco Systems, Dell EMC, Diablo Technologies, Echelon, Ericcson, Frame, Gen Z Consortium, Glue Networks, GlobalFoundries, Google (Nest), HP Inc. NVIDIA’s CEO and co-founder, Jensen Huang, is “putting Volta into the hands of researchers and scientists all over the world”. TITAN V (and Volta) is NOT the gaming-optimized follow-on to Pascal.Īll in all, the TITAN V appears to be a powerful, capable new offering from NVIDIA, great for simple entry into desktop-based machine learning training and inference. While some in the industry will love to bellyache about this decision and maybe even snipe about TITAN V gaming price-performance, just don’t. This means, Titan V’s transistor and memory subsystem improvements favor machine learning. And while TITAN V will do gaming just fine, in fact it’s the world’s fastest gaming GPU, it was designed first for machine learning training and inference, not for gaming. This includes gaming, content creation, deep learnings, and more. NVIDIA has done a great job making TITAN synonymous with the ultimate GPU for your PC. By combining the new memory controller with this HBM2 memory, TITAN V can guarantee 1.2 times delivered memory bandwidth, along with as much as 95% memory bandwidth utilization while running multiple workloads. NVIDIA says the TITAN V is fabricated on groundbreaking TSMC 12 nm FFN (FinFET NVIDIA) high-performance manufacturing process, and takes full advantage of Volta’s 12GB HBM2 memory subsystem. TITAN V also appears to deliver significant memory improvements. NVIDIA also says the Volta architecture is more efficient at HPC, thanks to its independent parallel integer and floating-point data paths. The Titan V also sports the same new Tensor Cores that are in Tesla GPUs which are geared specifically towards deep learning purposes. This allows for major boosts in FP32 and FP64 performance, within the same power envelope. Its Volta architecture underwent a serious revamping of the SM processor design at the core of the GPU, which should providetwice the energy of efficiencyPascal. In addition to the muscle, the Titan V is also highly energy efficient. This is different from Tesla that is targeted at server systems and deep learning appliances like the DGX Station. This immense amount of performance makes the TITAN V ideally suited users looking to explore computational processing for scientific simulation and other deep learning/AI applications on their desktop PCs. Machine learning workloads favor heavy-duty matrix math operations which require massive memory bandwidth and this is what TITAN V delivers.ĭriven by NVIDIA’s latest GPU architecture, Volta, NVIDIA says the TITAN V’s 21.1 billion transistors are capable of delivering 110 teraflops of performance (for reference, that’s 9x times the deep learning computing horsepower of its predecessor). This means the researcher doesn’t need a special server, storage or networking. TITAN V is targeted at machine learning scientists who want to conveniently buy the card and install it into their desktop PC. Targeting machine learning scientists who use desktop PCs ![]()
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