NVIDIA TITAN V is essentially the most highly effective graphics card ever created for the PC, pushed by the world’s most superior structure—NVIDIA Volta. NVIDIA’s supercomputing GPU structure is now right here on your PC, and fueling breakthroughs in each trade. NVIDIA TITAN V has the facility of 12 GB HBM2 reminiscence and 640 Tensor Cores, delivering 110 TeraFLOPS of efficiency. Plus, it options Volta-optimized NVIDIA CUDA for optimum outcomes.
640 TENSOR CORES An Exponential Leap in Efficiency Each trade wants AI, and with this large leap ahead in pace, AI can now be utilized to each trade. Outfitted with 640 Tensor Cores, Volta delivers over 100 Teraflops per second (TFLOPS) of deep studying efficiency, over a 5X improve in comparison with prior era NVIDIA Pascal structure.
NEW GPU ARCHITECTURE Engineered for the Fashionable Laptop Humanity’s biggest challenges would require essentially the most highly effective computing engine for each computational and information science. With over 21 billion transistors, Volta is essentially the most highly effective GPU structure the world has ever seen. It pairs NVIDIA CUDA and Tensor Cores to ship the efficiency of an AI supercomputer in a GPU.
NEXT GENERATION NVLINK Scalability for Speedy Time-to-Answer Volta makes use of subsequent era revolutionary NVIDIA NVLink high-speed interconnect know-how. This delivers 2X the throughput, in comparison with the earlier era of NVLink. This permits extra superior mannequin and information parallel approaches for robust scaling to attain absolutely the highest utility efficiency.
VOLTA-OPTIMIZED SOFTWARE GPU-Accelerated Frameworks and Functions Knowledge scientists are sometimes compelled to make trade-offs between mannequin accuracy and longer run-times. With Volta-optimized CUDA and NVIDIA Deep Studying SDK libraries like cuDNN, NCCL, and TensorRT, the trade’s high frameworks and functions can simply faucet into the facility of Volta. This propels information scientists and researchers in the direction of discoveries sooner than earlier than.
