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Deep Learning Performance with P100 GPUs

Deep Learning (DL), an area of Machine Learning, has achieved significant progress in recent years. Its application area includes pattern recognition, image classification, Natural Language Processing (NLP), autonomous driving and so on. Deep learning attempts to learn multiple levels of features of the input large data sets with multi-layer neural networks and make predictive decision for the new data. This indicates two phases in deep learning: first, the neural network is trained with large number of input data; second, the trained neural network is used to test/inference/predict the new data. Due to the large number of parameters (the weight matrix connecting neurons in different layers and the bias in each layer, etc.) and training set size, the training phase requires tremendous amounts of computation power.

To approach this problem, we utilize accelerators which include GPU, FPGA and DSP and so on. This blog focuses on GPU accelerator. GPU is a massively parallel architecture that employs thousands of small but efficient cores to accelerate the computational intensive tasks. Especially, NVIDIA? Tesla? P100? GPU uses the new Pascal? architecture to deliver very high performance for HPC and hyperscale workloads. In PCIe-based servers, P100 delivers around 4.7 and 9.3 TeraFLOPS of double and single precision performance, respectively. And in NVLink?-optimized servers, P100 delivers around 5.3 and 10.6 TeraFLOPS of double and single precision performance, respectively. This blog focuses on P100 for PCIe-based servers. P100 is also equipped with High Bandwidth Memory 2 (HBM2) which offers higher bandwidth than the traditional GDDR5 memory. Therefore, the high compute capability and high memory bandwidth make GPU an ideal candidate to accelerate deep learning applications.dell latitude e5540 battery

Deep Learning Frameworks and Dataset

In this blog, we will present the performance and scalability of P100 GPUs with different deep learning frameworks on a cluster. Three deep learning frameworks were chosen: NVIDIA’s fork of Caffe (NV-Caffe), MXNet and TensorFlow. Caffe is a well-known and widely used deep learning framework which is developed by the Berkeley Vision and Learning Center (BVLC) and by community contributors. It focuses more on the image classification and it supports multiple GPUs within a node but not across nodes. MXNet, jointly developed by collaborators from multiple universities and companies, is a lightweight, portable and flexible deep learning framework designed for both efficiency and flexibility. This framework scales to multiple GPUs within a node and across nodes. TensorFlow, developed by Google’s Brain team, is a library for numerical computation using data flow graphs. TensorFlow also supports multiples GPUs and can scale to multiple nodes.

All of the three deep learning frameworks we chose are able to perform the image classification task. With this in mind, we chose the well-known ImageNet Large Scale Visual Recognition Competition (ILSVRC) 2012 dataset. This training dataset contains 1281167 training images and 50000 validation images. All images are grouped into 1000 categories or classes. Another reason we chose ILSVRC 2012 dataset is that its workload is large enough to perform long time training and it is a benchmark dataset used by many deep learning researchers.dell optiplex 980 power supply

Testing Methodology

This blog quantifies the performance of deep learning frameworks using NVIDIA’s P100-PCIe GPU and Dell’s PowerEdge C4130 server architecture. Figure 1 shows the testing cluster. The cluster includes one head node which is Dell’s PowerEdge R630 and four compute nodes which are Dell’s PowerEdge C4130. All nodes are connected by an InfiniBand network and they share disk storage through NFS. Each compute node has 2 CPUs and 4 P100-PCIe GPUs. All of the four compute nodes have the same configurations. Table 1 shows the detailed information about the hardware configuration and software used in every compute node.

We measured the metrics of both images/sec and training time.

The images/sec is the measurement for training speed while the training time is the wall clock time for training, I/O operation and other overhead. The images/sec number was obtained from “samples/sec” in MXNet and TensorFlow in the output log files. NV-Caffe listed “M s/N iter” as output which means M seconds were taken to process N iterations, or N batches. The metric images/sec was calculated by “batch_size*N/M”. The batch size is the number of training samples in one forward/backward pass through all layers of a neural network. The images/sec number was averaged across all iterations to take into account the deviations.dell optiplex 990 power supply

The training time was obtained from “Time cost” in MXNet output logs. For NV-Caffe and TensorFlow, their output log files contained the wall-clock timestamps during the whole training. So the time difference from the start to the end of the training was calculated as the training time.

Since NV-Caffe did not support distributed training, it was not executed on multiple nodes. The MXNet framework was able to run on multiple nodes. However, the caveat was that it could only use the Ethernet interface (10 Gb/s) on the compute nodes by default, and therefore the performance was not as high as expected. To solve this issue, we have manually changed its source code so that the high-speed InfiniBand interface (EDR 100 Gb/s) was used. The training with TensorFlow on multiple nodes was able to run but with poor performance and the reason is still under investigation.

Table 2 shows the input parameters used in different deep learning frameworks. In all deep learning frameworks, the neural network training requires many epochs or iterations. Whether the term epoch or iteration is used is determined by each framework. An epoch is a complete pass through all samples in a given dataset, while one iteration processes only one batch of samples. Therefore, the relationship between iterations and epochs is: epochs = (iterations*batch_size)/training_samples. Every framework only needs either epochs or iterations so that another parameter can be easily determined by this formula. Since our goal was to measure the performance and scalability of Dell’s server and not to train an end-to-end image classification model, the training was a subset of the full model training which was large enough to reflect performance. Therefore we chose a smaller number of epochs or iterations so that they could finish in a reasonable time. Although only partial training was performed, the training speed (images/sec) remained relatively constant over this period.optiplex 390 power supply

The batch size is one of the hyperparameters the user needs to tune when training a neural network model with mini-batch Stochastic Gradient Descent (SGD). The batch size in the table are commonly used sizes. Whether these batch sizes are optimized for model accuracy is left in future work. For all neural networks in all frameworks, we increased the batch size proportionally with increasing number of GPUs. In the meantime, the number of iterations was adjusted so that the total number of samples was fixed no matter how many GPUs were used. Since epoch has nothing to do with batch size, its value was not changed when a different number of GPUs was used. For MXNet GoogleNet, there was runtime error if different bath sizes were used for different number of GPUs, so we used constant batch size. Learning rate is another hyperparameter that needs to be tuned. In this experiment, the default value in each framework was used.b173zan01.0


The right way to choose Throwback Jersey

North Carolina hasn’t were built with a player result in to the National basketball association immediately after his freshman winter considering Brandan Wright in 2008. Wright has agency: On Wednesday, Tony Bradley proclaimed he was staying in the National basketball association draft becoming the actual 2nd one-and-finished of Williams’ tenure at UNC.

Bradley has normally obtained the ability to end up being an NBA gamer. He was actually a McDonald’s All-United states and fringe several-legend sponsor out of school who typed in UNC for the reason that program’s primary enrolling gain simply because the 2014 lesson that listed Justin Jackson, Theo Pinson, and Joel Berry II. Decide one of the favored Throwback Jersey, High School Jersey or Cheap Basketball Jersey, to help with your crew.

Bradley didn’t go into a video game for UNC as a freshman, rather than forthcoming over counter lurking behind two former McDonald’s All-People in the usa who stayed all many years in Kennedy Meeks and Isaiah Hicks. With both equally Meeks and Hicks graduating, Bradley might have been the Tar residue Heels’ preferred frontcourt gamer then period and among the list of the best coming back sophomores in the united states.

As a replacement, he’s coming into the draft to begin with his guru professional. Bradley is at present projected to be a following-rounded choose by DraftExpress, at which he’s slotted at No. 42 for the Utah Jazz. Of all of the time frame judgments to your National basketball association draft, Bradley opting to result in UNC seems like it will enjoy the major ramification on then season’s state scenery in school football.

North Carolina was going to be in great shape following time even with no Meeks, Hicks, and departed junior legend Justin Jackson. Berry was to come back at matter defend, and Pinson went back relating to the wing for his or her senior conditions. Bradley could possibly have due to the Tar residue High heels one third star being a massive dude who could ranking indoors along with shield the paint.

Because he’s ended up, UNC is left with no need of a great deal of contingency method. There’s however Luke Maye, the first kind recommended stroll-on who was a legend for his computer game-winner with Kentucky inside Elite Eight. He ventures to get started at effectiveness forward. At center, it is a whole lot more unsure.

The two most likely options are inbound freshmen Garrison Brooks and Brandon Huffman. Brooks involved with UNC in Apr after getting discharged from Mississippi State. He’s a 6’10, 230-pound large person scored being the No. 120 player from the style of 2017 by Competition. Huffman is 6’9, 235 fat and it is perceived as a three-celebrity bring in.

To place this in perception: Last time of the year, Hicks was a to begin with-time starter as being a senior when located on the counter for three times as a former McDonald’s All-United states. Next season, UNC will often be getting into an authentic freshman who was not also a best-100 bring in in the type.

North Carolina will even now have a great squad guided by arguably the top end matter guard in america in Berry. But it’s difficult to imagine the High heels duplicating with your a thin and novice front side lines.

It is likely. Williams are now able to point out Bradley when he’s on your enrolling pathway and say, seem, it is possible to send freshmen to NBA, much too. Potentially that can assist UNC area other National basketball association-grade abilities in sponsoring and essentially be beneficial in the plan.

It may sound decent in theory, but there are reasons to be skeptical. Usually, the freshmen who wind up getting 1-and-carried out could have been 1-and-dones any place.

Consider UNC’s modern hiring of Kevin Knox, as an illustration. Knox most importantly select Kentucky. Annually from now when he’s a lottery select during the 2018 NBA write, John Calipari will indicate Knox as one other example of What Kentucky Can Perform For Your Needs. The fact is that he could have been a one-and-performed at UNC, or Duke, or Fl Status, or Mizzou, or another faculty in the country.

As of late, you will find many best senior high school online players are already famous brands long before they possibly go with a university. That is without doubt the fact for UNC’s finest targeted in recruiting right away: group of 2018 superstar Zion Williamson. Previous to he begins his elderly year of highschool, Williamson previously has Drake using his jersey. They have very nearly 700K Instagram visitors. He is a feeling for his dunking flexibility. Williamson may very well most importantly decide UNC, though it probably has minimal amount of to do with Bradley’s selection.

Might be it is completely different for that player scored through the 20s or 30s of his course as opposed to a certainly top notch creativity like Williamson. But usually, the main one-and-dones are observed a long time before they manufacture their university call.


What are evergreen webinars?

They are webinars whose topics are always relevant and interesting for a large number of attendees, no matter when and in what circumstances you run them. In evergreen webinars, you share knowledge that is always “fresh” and needed.

Why should you have a set of evergreen webinars?

To use them anytime you have no current topics to cover. They are also a great way to promote your business in a certain season or circumstances – e.g. summer holidays – or in your new product campaign.

Evergreen webinars are good for your SEO. You probably know what topics related to your business your customers search for. Include relevant keywords in your webinar and share the recording on your site, making it properly optimized for browsers. It will continually drive traffic to your site as the topic stays fresh for a long period of time.

With evergreen webinars, you can also develop your expert’s position. You share knowledge that’s always relevant and you have ready answers to questions your customers will keep asking.sell webinars online

Types of evergreen webinars


These are? How to…” guides, in which you teach people how to build, cook, fix, draw, or choose something, for example:

How to choose running shoes? If you sell sports stuff, teach customers how to choose equipment that fits their needs. No matter what current trends are, certain rules don’t change.
A quick guide to making stunning graphics in Canva. A social media expert can use their YouTube channel to host webinars on creating great content for social platforms.

How to pack your cabin luggage in 10 minutes. A webinar on how to quickly squeeze everything you need in a tiny bag will be much appreciated by customers of a holiday booking service or a luggage online store.best webinar services

Educational webinars

These are webinars in which you share knowledge on important topics a large number of your customers are interested in. For instance:

The most common reasons cats pee outside the litterbox. If you sell pet products make sure you have a series of pet-related webinars on your site. The topics can be pet care, pet food, common diseases and behavioral problems.

Spelling mistakes English language learners make. A language school can host webinars on common problems such as pronunciation or frequently confused words. You can promote your webinars during school entrance exams to drive traffic to your site or YouTube channel.

Craft beer. What every beer lover must know before they raise a pint. If you run a microbrewery invite your customers to attend a webinar on beer styles, the secrets of beer making or beer history.benefits of online education

Expert’s tips and tricks

These are guides in which you cover evergreen topics and give advice from your own experience. For instance:

3 alternative coffee brewing methods I have tested. A coffee online store with own roaster can invite customers to visit its site or social channels to watch webinars on coffee blends, latte art techniques and tea types.

10 ways of organizing your wardrobe I recommend. A lifestyle blogger can host webinars on timeless pieces of clothing every man or woman needs, types of fabrics and on how to take care of your clothes.webinars software free

What should you keep in mind to make your webinars truly evergreen?

Your webinar is to stay relevant for a long period of time so don’t say things like “I’ve been in this business for 3 years” or “I last used this trick 2 months ago”.

Don’t refer to current topics like a popular brand’s recent marketing campaign, the last presidential election or a famous celebrity wedding.

Don’t mention products that are popular now but may not be as popular in a few years’ time. So in a webinar on how to spend time outdoors with kids, skip the bit about Pokemon Go.

About ezTalks webinars

Regardless of the location,ezTalks Webinars enables you to host a video meeting or online discussion anytime. Here ezTalks offers the hottest tips and how-tos for Webinars in different industries.

ezTalks is the world's leading online video conferencing provider that enables you to connect with people anywhere and anytime. Integrated with HD video conferencing, audio conferencing, screen sharing, content sharing, remote control and other powerful features, it can be widely applied to all industries

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