DataBloomHighlighting deep support from a flourishing roster of GeForce partners, NVIDIA’s Jeff Fisher delivered a virtual keynote at COMPUTEX 2021 in Taipei Tuesday. Fisher, senior vice president of NVIDIA’s GeForce business, announced a pair of powerful new gaming GPUs — the GeForce RTX 3080 Ti and GeForce RTX 3070 Ti — and detailed the fast-growing Read article >
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SANTA CLARA, Calif., June 01, 2021 (GLOBE NEWSWIRE) — NVIDIA will present at the following events for the financial community: Evercore ISI Inaugural TMT ConferenceMonday, June 7, at 10:15 …
Situation:
I have a dataset (<class ‘tensorflow.python.data.ops.dataset_ops.MapDataset’>) which is a result of some neural network output. In order to get my final prediction, I am currently iterating over it as follows:
for row in dataset: ap_distance, an_distance = row y_pred.append(int(ap_distance.numpy() > an_distance.numpy()))
The dataset has two columns, each holding a scalar wrapped in a tensor.
Problem:
The loop body is very simple, it takes < 1e-5 seconds to compute. Sadly, one iteration takes ca. 0.3 seconds, so fetching the next row from the dataset seems to take almost 0.3s! This behavior is very weird given my hardware (running on a rented GPU server with 16 AMD EPYC cores and 258GB RAM) and the fact that a colleague on his laptop can finish an iteration in 1-2 orders of magnitude less time than I can. The dataset has ca. 60k rows, hence it is unacceptable to wait for so long.
What I tried:
I tried mapping the above loop body onto every row of the dataset object, but sadly .numpy() is not available inside dataset.map()!
Questions:
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My company is solving very specific task of semantic segmentation using small UNet and we need to speed up training. Our current workstation has single Tesla v100 and we are looking for new workstation with several A100 but can’t measure how much speed up we will get with the increase of GPU number with new Ampere architecture. The second question is do we need NVSwitch or NVLink for training UNet and what speed improvement it would give us. According to our budget we can possibly get DGX A100(40GB A100) or custom configuration without useless options for our task, for example NVSwitch. The only thing I find is NVidia Unet industrial performance but the evaluation has been done on DGX-1 and DGX A100 with NVLink/NVSwitch both so the impact of GPU interconnection is not obvious.
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Microsoft Azure has announced the general availability of the ND A100 v4 VM series, their most powerful virtual machines for supercomputer-class AI and HPC workloads, powered by NVIDIA A100 Tensor Core GPUs and NVIDIA HDR InfiniBand. NVIDIA collaborated with Azure to architect this new scale-up and scale-out AI platform, which brings together groundbreaking NVIDIA Ampere Read article >
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The streaming device with the most 4K HDR content available now has even more as Apple TV joins the lineup on NVIDIA SHIELD. Starting today, SHIELD owners can stream the Apple TV app, including Apple TV+, and its impressive lineup of award-winning series, compelling dramas, groundbreaking documentaries, kids’ shows, comedies and more. The Apple TV Read article >
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Content creators are getting a slew of new tools in their creative arsenal at COMPUTEX with the announcement of new NVIDIA GeForce RTX 3080 Ti and 3070 Ti GPUs. These GPUs deliver massive time savings for freelancers and creatives specializing in video editing, 3D animation or architectural visualization. In addition, HP and Acer announced new Read article >
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Several of the world’s top server manufacturers today at COMPUTEX 2021 announced new systems powered by NVIDIA BlueField-2 data processing units. While systems with NVIDIA GPUs are already available now with the option of adding BlueField-2 DPUs, many applications and customer use cases may not require a GPU but can still benefit from a DPU. Read article >
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NVIDIA today announced dozens of new servers certified to run NVIDIA AI Enterprise software, marking a rapid expansion of the NVIDIA-Certified Systems™ program, which has grown to include more than 50 systems from the world’s leading manufacturers.