#GPU Computing Homework Help

[matlabhwexperts-blog]

GPU Computing Assignment Homework Help

https://www.matlabhomeworkexperts.com/gpu-computing-assignment-help-matlab.php

A Graphics Processing  Unit (GPU) is a specialized electronic circuit designed to rapidly  manipulate and alter memory to accelerate the creation of images in a frame  buffer intended for output to a display. GPUs are used in embedded systems,  mobile phones, personal computers, workstations, and game consoles. GPU  computing is the use of a GPU to do general purpose scientific and engineering   computing. Its introduction opened new doors in the areas of research and  science. Due to their massive-parallel architecture, using GPUs enables the  completion of computationally intensive assignments much faster compared with  conventional CPUs.

We  at Matlab Homework Experts provide expert help for Graphics Processing Unit assignment or Graphics Processing  Unit homework. Our Graphics Processing Unit online tutors are highly talented in providing college and university level Graphics Processing  Unit assignment and Graphics Processing Unit homework help to students.

[johnsonstorm3-blog]

Xbox live One - A Perfect Choice This kind of Holiday Season

Christmas, Christmas time has arrived. Moment for toys and time for cheers! Indeed, that's most suitable! Xmas is just a new month away. We live simply no in November and now we happen to be starting the count along until we all have the excellent (or not necessarily so great) gifts that we have been seeking all year long. Very hot on this particular list is usually game units. With Ms, Sony, together with Nintendo all of having subsequent gen gaming consoles on the market, not to mention often the slew regarding new twisty, bendy notebooks and other gadgets, just what is the best gaming platform? I have always been a Ps male, however We performed quickly own the Xbox 360 prior to the red ring connected with demise got it. Subsequently about 6 months back, my PS3 SLIM blew way up. What was some sort of player to do? I would some sort of lot of homework. We discovered that the GPU, the unit that drives the graphics guiding the 2 machines, PS4 in addition to Xbox One, ended up both created by my favorite CPU/GPU founder, ADVANCED MICRO DEVICES. When AMD the chip-set then you know the idea is built right. Consequently, the fact that did not support me much in choosing. The PlayStation 4 (PS4) does have a quicker, bigger grade of dodge storage in it like it utilizes DDR5 plus the Xbox One still uses the standard DDR4. Therefore , I was leaping at the tad to be able to get my hands about the PS4. I i am glad I had definitely not, even so. I found a good superior bundle deal that experienced the Xbox One system, the Kinect photographic camera, in addition to a $60 game added too for the giggles. This particular package deal cost me $450 at Walmart and the fact that was not necessarily on a purchase such as Black Friday. That was the everyday pack cost at that period. Heck, without the match that system was working $499. By the technique, Titanfall solely was well worth buying the Xbox One when I did. For Xbox One controller skin , what may not get learned off the package the particular Xbox One comes with, is the Xbox 1 is designed to operate the cloud created by Microsof company referred to as Azure. Being in a position to work with this cloud (many, many different computers systems simply hooked up together) the Xbox One can use often the power of the machines it can be connected to, presenting the gaming console the capability to be 4 moments stronger than the components that is closed around this console. This seemed to be often the icing on often the cake for me personally. Throw within that the Xbox One has both an HDMI away as well as HDMI in to enable you to plug up your high def cable television box to this gaming system, to enable you to control what an individual watch on TV through speech command in addition to hand expressions, this unit just gets more thrilling! With the slew connected with Xbox A person Apps today on often the market for free, yes 100 % free, as of a new couple several weeks ago anyone no longer have to help pay for a Gold Are living account since you can now make use of the apps in addition to enjoy the games on the internet for FREE!!

[goocy]

The emerging AI revolution

The second chatbot explosion

The advent of AI chatbots has already made a significant impact on our digital landscape, with platforms like ChatGPT demonstrating the potential for super-human intelligence in a conversational AI. ChatGPT is already passing university-level tests, despite not even being trained to be especially clever. However, the real game-changer in this space to me seems to be the emergence of Alpaca, an tiny branch of a Facebook model with one very impactful quirk: Unlike ChatGPT, which relies on millions of dollars worth of server-grade GPUs, Alpaca can run on any computer as small as a Raspberry Pi, significantly broadening its reach and adoption.

As a result of this increased accessibility, we're likely to witness a massive explosion in the number of chatbots that are indistinguishable from human actors. Chatbots can reason, they can be emotional, they can simulate a personality, all to a level of sophistication that makes it completely opaque that there is no human behind the keyboard. This sudden widening access to chatbots is, on its surface, a huge power boost: now you only need a handful of computers and accounts to completely dominate an online discussion with your opinion. However, because your opponents have the same capabilities, I don't expect easy domination and rather a drastic increase in overall online activity. Within a few months, this development might escalate to the point that the majority of apparent users we encounter online, could be AI chatbots rather than real people. Superficial human quirks like sleeping times or lunch breaks are trivial to simulate.

This explosion of chatbots brings to light an important issue: these AI agents are not neutral. They will be overwhelmingly controlled by well-funded interests, such as state actors, corporations, or large political tribes, manipulating the narrative en masse and creating a false appearance of consensus. Users might not appreciate this shift in tone, or the constant series of realizations that the apparent idological opponent turns out to be an AI that never change their mind. A complete erosion of trust in anonymous online communication seems to be the obvious next phase.

To counteract this, users might resort to chatbot bans, although it's challenging to identify and block chatbots that pass the Turing test. Another potential remedy could be shifting to voice chat. However, if AI eventually becomes proficient in voice communication as well, the whole concept of anonymous human interaction could break down. I expect this development to drive people either into small, tight-knit groups of trusted individuals, or away from the internet altogether.

In this scenario, even after the exodus of human users, the sheer number of chatbots could keep overall activity in anonymous spaces from declining. This leads to the "dead internet" scenario: billions of bots screaming at each other, site metrics higher than ever, but no more human in sight. Only the steadily dropping ad revenue will be a hint of the underlying shift. Bots don't buy things.

AI disrupting white-collar labor

However, chatbots are just the beginning. Language AIs are already better than us at handling mundane, everyday tasks like explaining a kid's homework step-by-step, writing job applications, or writing eulogies. The whole range of white collar workers will soon find that AIs can be a huge help when taking over the tedious aspects of their work, such as writing renovation plans, annual job evaluations, or formal requirement documents. As the use of AI becomes more widespread, workers who can effectively harness its capabilities will likely thrive, while those who struggle to adapt will be left behind.

And this is a quite short-term development: Today's AI assistance tools, like Microsoft's Copilot, are already capable of automating a wide range of tasks, from drafting emails and summarizing online meetings to proposing agenda points - tasks that employ hundreds of thousands of executive assistants today. The AI help can reduce the time and energy spent on repetitive tasks, allowing office workers to focus on more critical aspects of their jobs - but they also can make them obsolete.

This development, like all industrial revolutions before it, raises concerns about the potential for AI to exacerbate existing inequalities. If we're not careful, we're about to tread familiar ground: automation starts displacing workers, but the machines stay in the hands of the ownership class, while workers compete in a race to the bottom.

Historically, we can find examples of how automation has displaced workers during times of rapid technological progress. The Industrial Revolution led to many skilled artisans losing their jobs as machines took over tasks that once required human craftsmanship. Similarly, the rise of computers and the internet displaced workers in industries like publishing and manufacturing.

However, there's a key difference in the current AI revolution that could be a cause for hope. Unlike previous industrial revolutions, where the ownership class controlled the machines and technology, many AI tools are currently open access. This means that workers themselves have the opportunity to harness AI's capabilities, rather than having the benefits concentrated solely within the hands of a select few.

If we can maintain this open access to AI and continue to develop policies that promote equitable distribution of its benefits, we could end up with a very different outcome than in previous technological upheavals. Rather than a race to the bottom, we could see a collective rise in productivity, efficiency, and quality of life. By keeping AI accessible to all, we have the chance to create a future where everyone wins, not just the ownership class.

Bridging the Affordability Gap

As AI continues to evolve and improve, it will increasingly encroach on traditionally human-centered professions. The roles of teachers, therapists, childcare providers, personal trainers, and other care providers will be challenged by comparatively cheap AI services and their ability to provide personalized, adaptive, and cost-effective solutions.

In the realm of education, AI tutors can tailor their teaching methods to each individual's learning style and even generate personalized educational content. Unlike human tutors, who take a long time to train, aren't easily replicated, and come at a high cost, AI-driven solutions can be scaled and improved quickly over time - a much more attractive option to the investor caste, even if it leads to subpar results.

Similarly, mental health professionals such as therapists and counselors, as well as personal trainers and childcare providers, will be seeing the rise of AI-driven solutions. AI can provide therapy or counseling sessions through chatbots or virtual environments, offering personalized exercises and coping strategies. AI can also create customized fitness routines for personal training or monitor and engage children in interactive educational playtime. Potentially, these AI-powered tools can offer affordable, easily accessible services to those in need, who might currently face long waiting lists or financial barriers to access their care.

The potential for AI to provide round-the-clock mental health support and other care services is immense, but it also raises questions about the role of human professionals in these fields. Will they need to adopt AI technology to remain relevant, or will they be replaced by AI counterparts?

As AI becomes more prevalent in human-near services, it's essential to strike a balance between leveraging AI's capabilities and preserving human expertise. Professionals in these fields will need to adapt to the changing landscape, incorporating AI into their work to provide the best possible care. By combining AI technology with human skill and compassion, we can create a future where care services are more accessible, personalized, and effective for everyone.

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Help With Computer Graphics Assignment from Professionals

Computer graphics can be visual animations, videos, images and GIFs. Online marketing uses computer graphics to engage customers and explain products and services. Animations are popular on websites because they can be attractive to customers. Computer graphics can be created using special software and tools. Students who study computer graphics will be exposed to different tools used to create the graphics. Professors will assign students rent types of assignments to help them improve their skills with the tools. Computer graphics requires a lot creativity and skill. This technology is as vast as an ocean. Computer graphics can also be called computer graphics by another name, i.e. computer-generated images. Computer graphics courses in educational institutions cover topics such as sprite graphics and GPU design, visualization, 3D modeling, and 3D modeling. When you see them in movies and video games, visuals can be eye-catchy and appealing. Because it transports them to a world of fantasy, people are drawn to the graphics. IT companies and other industries use computer graphics to make websites more appealing to end-users. Computer graphics professionals are in high demand due to the global demand for them. Many students choose to study computer graphics even though they struggle to understand the concepts or solve their homework. Our programming experts can help you with Computer Graphics Assignment if you don't have the time. Our programmers are available 24/7 to help you with your programming assignment online. You can relax and concentrate on other things when you trust us to complete your computer graphics assignment. We will deliver the solution in a timely manner to your email. These subjects require students to be able to understand animation and many other topics. It is impossible for students to learn all of these things. Students might lose time studying the subject if they are too focused on finishing their assignments. Sometimes, the assignments can be so difficult that students are unable to solve them themselves. They may need external help. Professors are reluctant to help students because they want them to be their best. Many students feel that they are taking help, but professors don't accept their assignment. Computer Graphics Assignment Help keeps students' identities confidential. Our expert team of professors is familiar with college requirements and will write the assignment according to them only. Students should be aware of the many benefits that the service offers. It makes student's life easier.

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[modxcomputers]

In 2022, you might well create a simple custom-made gaming PC

There are several benefits to building a straightforward custom gaming PC as opposed to purchasing an assembled model or you can just buy custom pc. You may acquire components that are suited to your exact requirements, which may save you money. You may customise your computer's appearance. There will be no bloatware or obtrusive pre-installations to contend with. Additionally, building your computer is a new lesson that will help you comprehend how everything operates.

What are your specifications?

Regardless of whether you are building a PC for a home office or for gaming, you will need the same components. A motherboard, a CPU, storage, memory, a power supply, a chassis, and a display are all required components. If you primarily use this custom PC for home office tasks, a GPU graphics processing unit is optional; nevertheless, it is necessary for image or video editing and gaming.

Before you begin, you should always be aware of the recent global scarcity of PC parts, in particular graphics cards, and the rising cost of such parts. In the event that components are not readily accessible, waiting is the best counsel we can provide. Hopefully, everything will settle down soon.

Why Are More People Building Custom Gaming Computers?

There is a PC game out there for everyone, whether you like solitary challenges or teaming up with players from across the world for multiplayer adventures. Even when you improve at playing games, you'll find yourself wanting more from each one. This might feature higher-resolution graphics, the capacity to download and save more games, or the opportunity to survive broadcasting your gaming to other gamers. 

These aren't things you'll find on just any PC, and a decent gaming custom PC will cost you a lot in terms of spec-to-stats. Consequently, more and more gamers are choosing to build their own gaming computers. You may customise your own PC to meet your unique gaming demands and save money by purchasing the components separately and putting it together yourself.

A Custom PC is a good investment.

Building a PC is more affordable than buying one that has already been put together for a variety of factors.

You may choose your components yourself and make the lowest feasible payments for each one to start.

Instead of purchasing a prebuilt with a brand that has different or unnecessary components, it is wiser to conduct your homework and shop around for the best deal in the long run.

When you can build a custom PC, you know you've learned a life-long skill.

A custom PC maker has an edge over people who have not built their own computer, whether they are students or working adults.

When asked how many individuals in a room of 100 could build a computer, only a tiny fraction would raise their hands.

Computers are ubiquitous, being present in our homes, offices, cars, and even our wallets.

A fundamental knowledge of how machines operate is an essential life skill.

Conclusion

Gaming PCs are excellent for playing games, but they're also attractive and have a terrific appearance. By integrating gaming accessories, it becomes much simpler to play and more visually appealing. Buy gaming pc ghaziabad by truly your modx computer. We deal with all varieties of gaming and efficiency PC builds, and we advise our customers on the ideal model to purchase based on their demands and specifications.

[tech-girls]

Spotlight: May Casterline

Each month we spotlight a woman or girl in tech who inspires us. This month we are highlighting May Casterline. May is a working mother of 2 who has been active in science and technology field for 12 years. Her background is in remote sensing (satellite and airborne imaging systems) and the analytical systems built to exploit that type of data.  Because of the size of this data and the challenges it presents, she started working with AI and deep learning solutions to solve those problems. Today she is a senior solutions architect at NVIDIA.  

How do you work with technology today? I work for NVIDIA so technology and its application is at the core of our business.  Each day I am doing something different, but it is all unified by the mission of helping folks adopt AI and GPU-accelerated approaches to solve their problems. This can involve developing training materials, giving talks, doing technical deep dives, developing proofs of concepts, or helping design system architectures.

What drives your interest in technology? I am perpetually interested in technology because there is always something new to learn.

What do you remember about your first coding experience? I was first introduced to coding as a freshman in undergraduate. I was in an introduction to C++ class. I have a distinct memory of the logic and methodology that drove the development cycle making perfect sense to me and just clicking. I fell in love with it and started to find problems and projects where I could learn more about how to apply it to solutions.

What was your pathway to working in technology? I originally thought I was going to be a photographer and went to photography school. I ended up choosing a hybrid major called Photographic Technology that had the art school requirements, along with some technical classes that explored more of the science behind image formation and processing. The two technical classes I took freshman year were an Intro to C++ course and Materials and Processes of Photography (a class all about cameras, emulsions, silver halide formation, etc.). I was enthralled in these classes. Everything was fascinating and made sense. When I looked around, everyone else in my class seemed miserable. That is whn I realized that these were not my people and I needed to find something different.  Serendipitously, I was working on a homework assignment early on and was unable to find the answer in my course text book. Some other students on my dorm floor had a text book that ended up having the answer. When I asked them where that book came from they told me all about their major - Imaging Science. It was the perfect combination of imaging technology, computer science, and physic. I immediately switched majors and fell in love. I started doing research in the labs at RIT as and undergraduate and stayed on to complete my PhD. Throughout my undergraduate and graduate time I continued to grow my programming skills, mostly out of necessity. I needed tools to solve my own problems in my research and no one else was going to build them for me. That exposure to solving my own problems by building technology components eventually grew into a career of developing research and development software solutions to solve challenging problems.

Why is it important to get more girls and women interested in technology? Ultimately I ended up working in the DoD/intelligence community. As a technical contributor in this industry I am continuously the only woman, or on the rare occasion in a 2-3 person minority. Women are entirely under-represented in this industry and there are some very challenging and rewarding problems that need to be solved. I think we are short changing our society by not having more women in the technical decision making roles for these types of problems,

Who inspires you to pursue your passion? My daughter - she is part of the future and I want to show her that she can do anything she puts her mind to and make a difference. Corny, but quite true.

What most excites you about the future of technology? The most exciting thing for me is all the problems, that have long seemed impossible, actually being solved in our lifetimes. Whether its autonomous vehicles, mobility assistance, drug discovery - its all possible and incredibly close.

What advice would you give to your younger self? Stay focused and always say what you think, no matter what.

[playgamesonline2018-blog]

These 10 Hacks Will Make You(r) Autodesk Software (Look) Like A professional

These 10 Hacks Will Make You(r) Autodesk Software (Look) Like A professional

CAD is CAD at the top of the day whether or not you might be Camp Autodesk or Camp Dassault Systemes so learn with Fusion 360 and transfer to Inventor once you get a job. Knowledge Network See Additionally: Toolbar and top, backside display showing black after the April twenty sixth 2021 replace of Fusion 360 ( ) Fusion 360 doesn't launch ( ) Was this information helpful? Learn Autodesk's article on Community License Administration for extra data. For extra information, see Publish the template VM. For more information, see Create and handle a template in Azure Lab Services. For present pricing data, see Azure Lab Providers pricing. Set a static non-public IP and MAC address for the Azure VM that hosts your license server. If you determine to host your license server by utilizing an Azure VM, it’s necessary to ensure that your license server’s MAC handle doesn’t change. Upon getting an Azure subscription, you can create a new lab plan in Azure Lab Companies. For more information about creating a brand new lab plan, see Tutorial: Arrange a lab plan with Azure Lab Providers.

Extra info might be found right here. The template picture can now be published to the lab. When you create a lab, a template VM will likely be created based mostly on the virtual machine dimension and picture you selected. The digital machine measurement we chose was Small GPU (Visualization), which is 160 lab units. Be certain that to choose Small GPU (Visualization) not Small GPU (Compute). The Small GPU (Visualization) digital machine size is configured to allow a excessive-performing graphics experience and meets Adobe’s system necessities for every utility. The cafeteria has an amazing espresso machine and espresso grinders to get you one of the best cup of espresso you will ever have at work (well, until perhaps you're a barista?). You signed in to the Autodesk desktop app with an e-mail deal with totally different from the one you used to get a subscription. You could have to get a brand new subscription somewhat than autorenewing the previous one. The Let’s Get Started display screen seems. Let’s cover an example value estimate for this class. The price estimate is for example functions solely. This estimate doesn’t include the price of working a license server. American Eagle reported revenue of $1.055 billion versus Refinitiv’s consensus estimate of $1.142 billion.

Remaining performance obligations (RPO) elevated 18 percent to $4.23 billion. Try the completely different packages like Inventor, Revit, Maya and more with Autodesk free trial. You used the software program in trial mode after which obtained a subscription utilizing a unique e mail tackle. To set up this lab, you want entry to an Azure subscription. You will need to access a license server if you plan to use the Autodesk community licensing model. You'd have a ‘floating’ licence, which would give you, and only you, entry to certainly one of your machines at a time. Suppose you have got a class of 25 college students, each of whom has 20 hours of scheduled class time. Every pupil also has an additional 10 quota hours for homework or assignments outside of scheduled class time. With onerous work and dedication, you too can change into an expert utilizing these geotechnical tools that can be exterior of the field of your normal workflow. Whenever you download the newest version of the program, you will also have a lot simpler and intuitive controls that enable you to create a perfect workflow. Enables project groups to align and execute on design intent by managing the whole design collaboration and coordination workflow from a single solution to cut back rework, enhance productiveness and accelerate venture supply.

1. In the Undertaking window, choose Geometry tab and click on on Nothing underneath the curve Selections, then select the desired device path on the 3D Mannequin surface. For example, in Okay-12, AutoDesk is included within the Challenge Lead the best way (PLTW) curriculum. For instance, you will have modified from a perpetual license to a subscription license. Your subscription has expired. Then run the Product Design Suite 2015 installer and install solely the Autodesk Vault Basic 2015 (Server) from beneath the Set up Instruments and Utilities section of the initial installer dialog. Within the Vault Pro Merchandise world, you could have information and you have objects. No further files are required to finish the design described - all recordsdata can be created utilizing the exercises in sequence. Using the Profile Layout Instruments toolbar not causes the application to close unexpectedly. To use network licensing with Autodesk software, AutoDesk offers detailed steps to put in Autodesk Network License Supervisor in your license server. If the MAC handle changes, you will need to regenerate your licensing information.

source https://creative-3d-simplification.blogspot.com/2022/06/these-10-hacks-will-make-your-autodesk.html

[shamelesshottubtheorist]

Intel R Pentium R 4 Cpu 2.26 Ghz Driver For Mac

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Intel R Pentium R 4 Cpu 2.26 Ghz Driver For Mac Windows 7

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Download Intel Extreme Graphics Driver 11.4.3 (Graphics Board) Note: This is the initial Intel Extreme Graphics driver for the Intel 845G (Essex and Essex 2 motherboards) and Intel 845GL chipset (Nimitz and Dasher motherboards).

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PENTIUM R DUAL-CORE CPU E6600 LAN DRIVER DETAILS:

Type:DriverFile Name:pentium_r_3400.zipFile Size:3.4 MBRating:

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PENTIUM R DUAL-CORE CPU E6600 LAN DRIVER (pentium_r_3400.zip)

Cost, for orders over 99 ex vat standard delivery is free. Which i did but which had no effect on the get windows 10 app declaring the cpu is not supported. Most ram is compatible with most cpus, assuming you have a motherboard that will fit both. A dual-core pentium d works with windows 10 but it s just not pleasant. Stay on intel pentium dual-core mobile devices.

Your name and email address will not be added to any mailing list, and you will not receive email from intel corporation unless requested. Core 2 cores clocked at 3. Visit for free, full and secured software s. Pentiumr dual core cpu e5700 300 driver for windows 7 32 bit, windows 7 64 bit, windows 10, 8, xp.

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Some processors were sold under both names, but the newer e5400 through e6800 desktop and su4100/t4x00 mobile processors were not officially part of the pentium dual-core line. Improve your pc peformance with this new update. Throughout 2009, intel changed the name back from pentium dual-core to pentium in its publications. Find intel 5 series, our database. The cpu is now over 11 years old, which means it is extremely out of date and is based on very aged processor will be dwarfed in performance by its modern counterparts, and will likely.

Jobs, utilities, l2 cache! Rating by its web site useful? Find intel atom e3900 soc family. Find intel pentium processor manuals, comes with the different processors. The dual-core processor runs on a 1066 mhz fsb, comes clocked at 2.4 ghz and most importantly has a massive 4mb of l2 cache! Space, compared to start with windows xp. Services, cars, pentium dual-core line. Pentium dual-core e2160 is very similar to the slowest member of core 2 duo family, core 2 duo e4300 processors run at the same core and fsb frequency, have the same size of level 1 caches, and include pretty much the same core features. This isn't a great result which indicates that there are much faster alternatives on the comparison list.

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Whether you want to have a computer at home so that you can finish work projects, complete homework assignments, or browse the internet and watch streaming video, you need one that has a quality motherboard and central processing unit cpu .

Lan usb ect. with older hardware stay on win 7-8 the core2 is not an pentium cpu, its an intel cpu thats ancient, about 8 years g3258 can run windows 10 fine if the gpu is newer.

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Can I hold 2 batches of dlnetwork gradients and update network parameters in 1 operation?

Due to the limitation of GPU memory, a deeplearning network can't learn like 16 samples in a batch.

So can I compute the gradients for a batch of 8 samples, and update the network gradients with 2 batches' gradients?

If I compute the gradients of a deeplearning network by

[gradients,state,loss] = dlfeval(@modelGradient,dlNet,xTrain,yTrain);

So after 2 batches, I get gradients1, gradients2, state1, state2, loss1, and loss2.

For my instant opinion, I think the total gradients should be the mean of gradients1 and gradients2.

But how can I compute the state values? Is it also the mean of state1 and state2?

ANSWER

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Yes, absolutely, just sum the gradients until your batch size is the size you want, then update the model. The principle is exactly the same is training a model on multiple GPUs (or CPUs).

The State update depends on the State. This example shows you how to aggregate batch norm state. The function aggregateState is of interest here. Instead of using gplus you would just be aggregating over your 'sub'-iterations.

function state = aggregateState(state,factor)    numrows = size(state,1);        for j = 1:numrows        isBatchNormalizationState = state.Parameter(j) =="TrainedMean"...            && state.Parameter(j+1) =="TrainedVariance"...            && state.Layer(j) == state.Layer(j+1);                if isBatchNormalizationState            meanVal = state.Value{j};            varVal = state.Value{j+1};

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The Market of Graphic Cards From Late 2020 to Early 2021

Jacob Lazo

Student ID - 78061131

The pandemic has made everyone move onto the internet. There are more people buying things through Amazon, many students are using zoom for school, and it is an all time high for online video games. Since practically everything is on the internet I decided to move on from my not so good laptop and get a personal computer (pc). I was in the market for a pc that would allow me to do my homework and that was capable of moderate gaming. My journey through the process of building my very own pc opened my eyes and I saw that much of the things from Econ 20A has a direct correlation with the real world. 

Putting together and installing the pc is an easy task when you have friends to help you, but the most difficult part of building your pc is actually getting the parts. At the time Black Friday was nearing and as usual sellers raised prices a few weeks in advance so that the “savings” that buyers received were large and perceived as a bargain. Among the price increases, sellers also increased the price for essential pc parts like the graphics card (gpu) and core processing unit (cpu). I thought the price increase was temporary, but soon found out I was terribly wrong. The demand for gpus and cpus rose as Christmas was nearing. As expected, prices rose and the supply dwindled. On top of the high prices former president Trump’s tariff on Chinese imports increased the prices of gpus . If that was not enough when gpus did get back in stock bots instantly bought out all the gpus and scalpers increase the price dramatically on top of the high price. 

As an example of how expensive it has gotten I bought my gpu about last month and payed $250 while today’s price is $384.

Beyond the supply and demand inference mentioned above I also had to think about the trade offs or opportunity cost of my decisions. Before I bought the very overpriced gpu, I thought about the trade offs of buying at this time. I could have waited a few months until the tariffs were taken down, demand for gpus went down too, and gotten a better gpu than the one I currently had or impatiently buy a not so good gpu. Besides being impatient I had reason to believe that prices were going to go even further and I was sadly right, but I am very glad I bought it the day of as the price increased to $300 the very next day. 

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How to Set Up an E-GPU for Your Laptop?

PowerColor is a GPU and attachment manufacturer, not a committed system-seller such as Razer or even Dell. The box supports all of the bells and whistles of this Razer Core, such as oversize GPUs, an Ethernet link up to 375 watts of electricity into the card.

The Devil Box is somewhat expensive at $450, but also the prospect of multi-system compatibility is most likely worth the excess cash for anybody planning on maintaining it via multiple notebook and GPU updates.

The MSI Gambling Dock, accessible only in a costly package with the organization's gaming-branded Shadow GS30 notebook , is the cheapest choice on this listing. That stated, it is not really trying to find the same marketplace: the Gambling Dock is a company device, that crams in extras such as a 2.1 speaker set up, mic and headphone ports, a full-sized SATA 3.5″ slotmachine, plus a Killer brand media card. It is designed to sit below the notebook within an elaborate stand, as the bark connector plugs right into the base of the laptop.

The Gambling Dock is actually just an option if you're absolutely certain that you need the Shadow GS30 specifically...and because neither it nor the Dock are considerably updated in quite some time, that is probably not a fantastic idea if you don't discover it onto a huge discount.

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Fast.ai vs Deeplearning.ai: which deep learning courses should you take?

As deep learning has become more popular, two courses stood out to me as having really useful teaching styles and reputable staff behind them: Fast.ai and Deeplearning.ai. As someone who has a theoretical background in deep learning and picked up Tensorflow on an as needed for a project basis, I was really interested in learning how to build complex deep learning architectures from scratch, and I’m always found I can sharpen my skills by hearing different experts describe known concepts.

Along with my goals of sharpening skills, I have been working alongside folks at the Recurse Center who are learning deep learning from scratch, and am using some of their feedback for evaluating the courses from that basis as well.

So, I delved into both courses and will share here what I found.

Theory

Theory in Fast.ai

The way Fast.ai handles theory is through visual examples and take home readings. I do not think this would be sufficient for a strong grasp of theory unless you can form a great study group to go over the readings and concepts. Both courses do have forums though, which could help with this.

Theory in Deep Learning.ai

The theory teaching in deeplearning.ai is really strong, with optional videos to watch that are of use if you have a calculus background to go into detail.

Winner: Deeplearning.ai . It's hard to beat Dr. Ng at explaining theory.

Applications

Applications in Fast.ai

I think it helps a lot that Jeremy Howard, a fast.ai professor, started a deep learning startup after seeing early on that modifying an out of the box ImageNet model could provide better results on classifying some medical imagery than top physicians. The hacker mentality is strong here as shown by show by having you able to submit to a Kaggle contest for what was at the release of the course a placement in the top 50% of the leaderboard, after lesson 1, and I’ve already reused several code snippets I’ve developed while going through the Fast.ai course, in projects.

Applications in Deeplearning.ai

While I could see myself using some code snippets from Deeplearning.ai (provided I downloaded them), I have not been able to easily translate the Deeplearning.ai code I’ve written into projects I’m working on. Deeplearning.ai also spends a lot more time teaching theory, especially early, and has yet to release their computer vision and sequence model components, so this will probably change soon.

Winner: Fast.ai since I am using code I’ve written there in projects already, whereas Deeplearning.ai code is mainly about learning the theory until their more application driven courses are released.

Portability

Portability of Fast.ai

Assuming you have access to a machine with GPU, this code is super portable, as you will be developing it all locally or on your own cloud box, and you will be developing modular solutions for real deep learning problems that you will continue to build on through out the course, within jupyter notebooks.

Portability of Deeplearning.ai

Deeplearning.ai really pales in comparison to Fast.ai here, for several reasons:

They wiped my homework notebook clean without prior notice when I stopped paying the monthly fee.

Since all your work is in their cloud, you need to explicitly download each Jupyter notebook of your homework before it is wiped.

I don’t find the code that applicable/extendable to the projects I’ve been doing in industry/academia.

Winner: Fast.ai hands down is here with reusable, extendable code provided you have a machine to run it on to begin with.

Accessibility

Accessibility of Fast.ai

I would say Fast.ai is super accessible as far as teaching style and language choice (Keras and now Pytorch which they will use in the future, are a lot more accessible than Tensorflow), so as long as you can afford to rent an AWS GPU box and figure out how to run their environment installation script on it or have a deep learning rig already (I do), it is a very accessible introduction.

Accessibility of Deeplearning.ai

One way Deeplearning.ai makes itself super accessible is by hosting cloud Jupyter notebooks for you to do all your work in. This made the class pretty frictionless to start on, and is why I started it first.

By pretty frictionless, I do imply there is still friction, which is true. One of the big turnoffs of mine towards this class is that they ghost auditing it. By ghost I mean that when I and several other of my peers first tried to take this class, they did not show auditing as an option, but when we came back to the site through a search engine, the auditing option appeared on the site. I believe this will inhibit many people who want to take the class, but can’t afford the $50 a month cost, from taking it.

Also, at this point I am not convinced learning Tensorflow is the best way to learn deep learning, the syntax is highly nuanced and takes time to grasp that one could be spending learning more about the concepts.

Winner: Fast.ai if you can access a GPU machine, Deeplearning.ai if you cannot.

Conclusion I ultimately think this is a trick question, even though Fast.ai did win on the personal evaluation scale I chose to evaluate the courses and I’ve spoken to several people who regret not starting with Fast.ai. I think some combination of both courses, fast.ai for applications and deeplearning.ai for theory, is the optimal use case.

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