Questions tagged [hardware]

For questions involving, but not exclusively about, hardware. (Please use the "hardware-evaluation" for questions exclusively about analysis of hardware components.)

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23 views

Is it possible to put embedded ML in something so low-latency-demanding as a guitar pedal?

I read the manual for a multi-mode delay pedal, particularly how it "studies" your playing for reverse mode. I don't have the spec, but I doubt that is meant literally; if I had to guess, &...
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Are there any cheap alternatives to NVIDIA hardware coming out in the near future? [closed]

Are there any cheap alternatives to NVIDIA hardware coming out in the near future? Like ASIC or FPGA based PCI-E cards, etc supporting popular libraries which have similar performance to high-end ...
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How does optical computing work and deal with nonlinearity?

This article states that: One of the algorithms that photonics is very good at implementing is matrix multiplication But how are parameters stored and updated(in backpropagation)? One more ...
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Multi user DL trainings: VMs VS Multi-seat configuration

For a project of Deep Learning for Detection algorithm (for e.g., improving YOLO) implying 4 users using the same hardware, is it more efficient to set the environment as each user has his own session ...
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1answer
26 views

Best Camera and protocol for embedded real time CNN project

I'm looking to develop a stand-alone real-time outdoor imaging CNN application, and I can't wrap my head around the myriad of camera options and their communication protocols. The target is a Linux ...
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1answer
197 views

What kind of hardware and software are required to build an AI system? [closed]

What kind of hardware (processor, memory, graphics card, etc.) and software are required to build an AI system? How do we go about linking each and every one of them to their proper place and function?...
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Quantization techniques and new GPU architectures [closed]

Quantization means using low resolution formats for some variables some of the time: binary (e.g. BinaryConnect), ternary, etc. The Turing architecture recently introduced by Nvidia is much faster ...
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2answers
102 views

Necessity of GPUs and hardware minimum specs for Deep Learning?

I’m doing some research into what hardware I need and what hardware I have available in college for a final year project. The project is designing a self driving car/computer vision system inside a ...
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1answer
157 views

Will quantum computing have any kind of effect on the development of AI? [duplicate]

Recently, according to some reports Google achieved something called 'Quantum Supremacy'. Whether its true or not remains to be seen. But my question is does Quantum Computers or the principle they ...
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1answer
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GPU/TPU acceleration for neural networks with various network topologies

I was thinking about different neural network topologies for some applications. However, I am not sure how this would affect the efficiency of hardware acceleration using GPU/TPU/some other chip. If, ...
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2answers
2k views

Should I use the Threadripper 2920X or Ryzen 7 3700X? [closed]

Update 2 The OS I'm using is Windows 10, since we have WSL, I also use Ubuntu to run the code. The code is written in Python. I know there are thousands of factors which affect the final performance ...
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2answers
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Why did ML only become viable after Nvidia's chips were available?

I listened to a talk by panel consisted of two influential Chinese scientists: Wang Gang and Yu Kai and others. When being asked about the biggest bottleneck of the development of artificial ...
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2answers
191 views

How long it takes to train face recognition deep neural network? (rough estimation)

If I use a desktop PC with a GPU, how long it might take to train face recognition deep neural network on let's say dataset of 2.6 million images and 2600 identities? I guess it should depend on ...
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1answer
35 views

Edge AI device to run inference

I'm trying to figure out what's the best way to get a trained model that does facial detection to run on a camera that's connected to a computer and perform inference. Since I don't need the device ...
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0answers
97 views

What does the CM1K chip (which uses ZISC) exactly do?

There's been a lot of apocalyptic hype (on the media) about CM1K and other similar technologies. Elon Musk has voiced fears about it taking over the world, which unfortunately are not unfounded. My ...
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1answer
99 views

What are the technological challenges that AI faces today?

I am writing a field report on AI. I was wondering what the technological challenges are that AI is facing today. I have written the following so far. AI needs common sense like a human common AI ...
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2answers
2k views

Does fp32 & fp64 performance of GPU affect deep learning model training? [closed]

I am purchasing Titan RTX GPU. Everything seems fine with that except float32 & float64 performance which seems lower vis-a-vis some of its counter parts. I wanted to understand if single ...
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1answer
89 views

What are the aspects that most impact on the inference time for neural networks in embedded systems?

I work with neural networks for real-time image processing on embedded softwares and I tested different architectures (Googlenet, Mobilenet, Resnet, custom networks...) and different hardware ...
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2answers
75 views

Tips for keeping the distribution of weights normal

I am working on a project where the Neural Network weights must be quantized on 8 or 16 bits for an embedded platform, thus I will lose some precision. Since our platform does not have floating point ...
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1answer
29 views

Does software remain even when hardware is demolished?

For example, if I constructed a neural network and the computer running it where to be demolished, is the information/program of the neural network still an existent entity within or outside the ...
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1answer
81 views

Are commercially available neural ICs digital?

Apparently, one can buy a special-purpose integrated circuit (an IC like this one, for instance) to host a convolutional neural network. QUESTION Is such a circuit digital? Except for digital random-...
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0answers
170 views

Is PCIe the bottleneck in a deep learning GPU system, so it makes sense to choose Nvidia NV-Link over more Tesla V100 graphics cards? [closed]

I'm considering a GPU system for deep learning applications, mainly for training models with large datasets. So I'm not sure whether it makes sense to choose Nvidia NV-Link over more Tesla V100 ...
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1answer
102 views

Which artificial intelligence algorithms could use tensor specific hardware?

AI algorithms involving neural networks can use tensor specific hardware. Are there any other artificial intelligence algorithms that could benefit from many tensor calculations in parallel? Are ...
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2answers
147 views

Are artificial networks based on the perceptron design inherently limiting?

At the time when the basic building blocks of machine learning (the perceptron layer and the convolution kernel) were invented, the model of the neuron in the brain taught at the university level was ...
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7answers
2k views

If digital values are mere estimates, why not return to analog for AI?

The impetus behind the twentieth century transition from analog to digital circuitry was driven by the desire for greater accuracy and lower noise. Now we are developing software where results are ...
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1answer
118 views

GPU to train object recognition neural networks [closed]

I'm starting to play around with python neural networks, mainly for object recognition like this one: https://github.com/huangshiyu13/RPNplus. I plan to train more networks with more kinds of objects. ...
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1answer
2k views

Thoughts on Apple Mac Pro vs GCP/AWS for Deep Learning? [closed]

I've been oogling the Mac Pro from Apple with loaded specs. Check it here if unfamiliar. I'm curious to hear anyone's thoughts of the computer for deep learning/machine learning applications vs ...
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3answers
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CPU preferences and specifications for a multi GPU deep-learning setup [closed]

For a multi (4xTitan Xp) GPU deep learning setup what kind of CPU is preferable? Specifically I am comparing: Intel Xeon E5-2620 with 8x2.1GHz 20MB L3 Cache Intel Xeon E5-1620K with 4x3.5Ghz 10MB L3 ...
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4answers
122 views

Could a large number of interconnected tiny turing-complete computer chips be patterned across a wafer to simulate a programmable neural network?

The Intel 8080 had 4500 transistors and ran at 2-3.125 MHz. By comparison, the 18-core Xeon Haswell-E5 han 5,560,000,000 transistors and can run at 2 GHz. Would it be possible or prudent to simulate a ...
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1answer
193 views

Using NVIDIA VOLTA V with Mac or Windows externally [closed]

I have a Macbook Air and Asus ROG 702 with a built in GeForce 1070 GPU. I'm considering getting an NVIDIA Volta for AI applications (tensorflow / pytorch) to run on either the mac or windows. Would ...
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2answers
193 views

What is the difference between a normal processor and a processor designed for AI?

What is the difference between a normal processor and a processor designed for AI?
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1answer
878 views

Who manufactures Google's Tensor Processing Units?

Does google manufacture TPUs? I know that google engineers are the ones responsible for the design, and that google is the one using them, but which company is responsible for the actual manufacturing ...
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1answer
1k views

Are more than 8 high performance Nvidia GPUs practical for deep learning applications?

I was prompted towards this question while trying to find server racks and motherboards which are specialized towards artificial intelligence. Naturally I went to the SuperMicro website. There the ...
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2answers
532 views

What is difference between edge computing and federated learning?

I recently read about federated learning introduced by Google, but it seems to be like edge computing. What is the difference between edge computing and federated learning?
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1answer
50 views

If we achieve sentience using mutable hardware, will it be possible to make a copy of that “brain” and its active state?

Hardware comes in two forms, basically: immutable, such as RAM, and mutable, such as FPGAs. In animals, neurological connections gain in strength by changing the physical structure of the brain. This ...
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4answers
739 views

Are we technically able to make, in hardware, arbitrarily large neural networks with current technology?

If neurons and synapses can be implemented using transistors, what prevents us from creating arbitrarily large neural networks using the same methods with which GPUs are made? In essence, we have ...
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4answers
3k views

How does using ASIC for the acceleration of AI work?

We can read on Wikipedia page that Google built a custom ASIC chip for machine learning and tailored for TensorFlow which helps to accelerate AI. Since ASIC chips are specially customized for one ...
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3answers
3k views

How powerful a computer is required to simulate the human brain?

How much processing power is needed to emulate the human brain? More specifically, the neural simulation, such as communication between the neurons and processing certain data in real-time. I ...
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1answer
170 views

Are there any microchips specifically designed to run ANNs?

I'm interested in hardware implementation of ANNs (artificial neural networks). Are there any popular existing technology implementations in form of microchips which are purpose designed to run ...