#NVIDIA 12GB GPU for Machine Learning

[lexart-io]

hi! I'm a fan of your work and am trying to learn ai myself, could you tell me a bit about your process? keep up the good work :D

thank you! everything i do these days is rendered in automatic1111 stable diffusion, run locally on my computer (on my nvidia rtx 3060 gpu w/ 12gb of vram). i train my own base models with kohya trainer XL and LoRA models with kohya LoRA trainer XL, both of which i usually run on google colab (on an nvidia a100 gpu because training models is a lot more resource intensive than rendering images).

most of what i do is less about the text prompt and more about the models used. in fact, i tend to recycle through a lot of the same text prompts over and over (with only minor changes to them) as i test out the models that i've trained. i think the most creative part of working with ai is in training models. text prompting is just the surface of it, but training ai is where you're really starting to create something that no one else can exactly replicate (unless they literally steal your dataset and settings). it is an extraordinarily fascinating form of creative expression that is unlike anything in human history... basically wrangling a blank slate machine intelligence to do your bidding by teaching it.

i do a lot of experimenting with the datasets that i use to train models. some are trained on more specific subjects or aesthetics, while others are trained on more symbolic concepts. then i combine these models when rendering images (the nice thing about LoRA models is that you can combine many models in a single text prompt). when i find combinations that seem particularly cool, i'll render a whole series of images and use those as a dataset to train a new model. then i'll combine that model with other models and sort of continue this evolutionary process of training and retraining models, using datasets comprised mostly of previously rendered images.

the datasets for my earliest models started with things like this (i would just slowly collect random cool images that captured a vibe that i liked, categorize them with other similar images, and eventually train a model on that specific vibe):

whereas now they're usually trained on images i previously rendered that share a specific vibe.

training models is definitely an art form itself... a lot of very delicate settings, how/if the dataset is tagged (the process of describing what is in each image to help the ai identify what it is analyzing during training), the specific images that comprise the dataset (1 bad/confusing image can sometimes really negatively impact the resulting model), etc. this is a whole HUGE subject that i could write FOREVER about, but i'll spare you (and myself) the endless wall of text haha.

anyway, some final gritty details worth mentioning about the workflow of actually rendering images and getting as much coherent detail as possible out of it: when i render something i like in automatic1111, i'll usually re-render it with hires fix using the LDSR upscaler to upscale it x2. some models don't play nicely with upscaling (and things can come out warped), so i'll either try again at x1.5 or x1.25 or try reducing the denoising strength (i typically like to keep it around 0.5). assuming the model(s) used do play nice with upscaling, i'll sometimes then send it over to the "img2img" tab and upscale it again x2 using the "SD upscale" script with the LDSR upscaler (denoising set to around 0.3 here). occasionally i'll upscale it x4 one last time using Real-ESRGAN (and then resize it down to something normal, since by this point the image resolution can exceed 10,000x10,000 pixels lol), which can help to smooth out any rough textures. the final step is making any last adjustments in photoshop - things like contrast or cleaning up noise / stray pixels.

hope this helps and hope it isn't too much of a mess to read haha. i really tried to condense as much of my process as i could into something as short as possible (i actually deleted 3 paragraphs during this because it was getting way too deep and i don't want to burden anyone with a boring novel of overly specific details). there are a lot of tutorials out there regarding everything i've mentioned here; reddit and youtube are probably the best resources. if you have specific questions on anything though, feel free to reach out! i'm always down to help folks get into this.

[godssilliestgirl]

It's actually really simple. All you have to do is find a trans woman and ask her and she can interpret the jargon into human readable language. Watch this

AMD Ryzen 5 7600X 6 core 12 thread 4.7ghz performance clock 5.3ghz performance boost clock, 2x16GB DDR5 4800mhz CL38 ram, Gigabyte Windforce OC RTX 4070 SUPER 12GB GDDR6X CCLK 1980MHZ BCLK 2505MHZ 2TB Samsung 980 PRO M.2 NVME SSD: midrange PC that will run all your programs either reasonably quickly or blindingly fast depending on the workload of the program. You know how I know this? Ryzen 5 means midrange. Nvidia gpus ending in 70 means midrange. Combined this is midrange. Midrange is the best adjective for computers cause it means you're usually in the sweet spot for performance to price ratio. Realistically unless you're into machine learning or data science or editing 8k videos midrange is a catch all. It *will* run and it will *not* be slow.

Anyways theoretically there is data you could look into that supports the claim of "Ryzen 5 -70 series card means midrange" but unless amd and Nvidia both teamed up to fuck with this post specifically that should hold true without me looking.

If you want to look at some useful numbers, check the recommended system requirements then go to passmark's website and compare the recommended components to whatever you're looking at online. To oversimplify things greatly, when looking at CPU benchmarks, the smaller single threaded number is more accurate for comparing how it will perform in games relatively to each other while the larger multi threaded number is more accurate for comparing performance for things that aren't games (there are frequent exceptions to both of these but don't worry about that) as for GPUs, once again, oversimplifying greatly, the DirectX numbers are your gaming numbers and GPU compute is your everything else numbers.

Also never trust anything you see on userbenchmark.com, their 2019 April fools joke never ended and they are not a reliable source

why is shopping for computer shit so difficult like what the hell is 40 cunt thread chip 3000 processor with 32 florps of borps and a z12 yummy biscuits graphics drive 400102XXDRZ like ok um will it run my programmes

[govindhtech]

AMD Radeon RX 6700 Specs Gaming, Benchmarks And Pricing

GPU RX 6700

RDNA 2 powers the mid-range AMD Radeon RX 6700's 1440p gaming. We'll review its attributes, performance, and other details.

Architecture and Features

The new RDNA 2 design boosts performance per watt by 54%.

Power consumption and memory delay are reduced with 80 MB of Infinity Cache on-die cache.

DirectX 12 Ultimate support: Allows variable rate shading and ray tracing.

Support for PCIe 4.0 ensures faster data transfer.

Support for AV1 Decode improves video streaming.

With compatible Ryzen CPUs, AMD Smart Access Memory boosts performance.

Upscaling in AMD FidelityFX Super Resolution (FSR) speeds up frames.

Advantages

Modern games run smoothly in 1440p.

Effective Design: RDNA 2 outperforms per watt.

Rich Features: Supports Smart Access Memory, FSR, and Ray Tracing.

Competitive pricing: Has good performance-tier value.

Disadvantages

Limited VRAM: 10 GB may not be enough for higher-resolution games.

Ray Tracing Performance trails NVIDIA in ray tracing workloads.

AI workloads aren't optimised for machine learning.

Ray Tracking

Radeon RX 6700 includes 36 Ray Accelerators—one per CPU—to improve game and app lighting, shadows, and reflections. Midrange GPUs can ray trace, although NVIDIA's RTX series has superior RT cores and AI-powered DLSS.

Ray tracing works well at 1080p and sometimes 1440p on the RX 6700, but higher settings may require downscaling or AMD's FidelityFX Super Resolution (FSR) to maintain frame rate.

Finally, the RX 6700's ray tracing improves budget gamers' and producers' graphics.

3D Render

AMD HIP enhances Blender GPU rendering.

Many engines support OpenCL, including LuxCoreRender and Radeon ProRender.

High-resolution textures, complicated settings, and large models work well on 10GB/12GB VRAM.

These times are equivalent to RTX 3060 12GB but slower than 3070/3080 in CUDA-optimized renderers.

Limitations

CUDA-dependent OctaneRender and Redshift are disabled.

Multi-GPU systems for CUDA-optimized apps are slower than NVIDIA.

Video Editing

Editing Software Support

Excellent OpenCL/GPU acceleration, 4K timeline playback, and DaVinci Resolve exporting.

Premiere Pro: GPU acceleration, smooth editing and previewing, but slower encoding/export than NVIDIA.

Good timeline scrubbing and basic motion graphics with After Effects. Works well with light-to-moderate compositions.

Conclusion

AMD Radeon RX 6700 is a good 1440p GPU for its price and performance. Though its ray tracing and AI are poor, its features and efficiency make it a market contender.

[componentplanet]

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Dell Vostro 15 7500 Intel Core i7-10750H 15.6-Inch 1080p Laptop w/ Nvidia GeForce GTX 1650 GPU, 8GB DDR4 RAM and 256GB NVMe SSD ($969.00)

The new Vostro 15 7500 laptop is a true jack-of-all-trades. Dell’s Vostro systems are oriented as business solutions, and this system is no different, but it also has fairly strong gaming capabilities. Its 100 percent sRGB display is also well suited for editing images. No matter what you need a laptop for, this system should fit the bill. Currently, you can get this system from Dell with a hefty discount that drops the price from $1,712.86 to just $969.00.

Samsung Galaxy Note 20 Ultra 5G 512GB 6.9-Inch Unlocked Smartphone ($1,099.99)

Coming equipped with Qualcomm’s Snapdragon 865+ SoC, the Galaxy Note 20 Ultra should be exceptionally fast with performance on par to today’s latest flagship phones. The phone also utilizes a Dynamic AMOLED 2X Infinity-O display with a 120Hz refresh rate that measures 6.9-inches diagonally. This model also has 12GB of RAM, a 4,500 mAh battery, and 512GB of storage. For a limited time you can get this new cutting edge smartphone from Amazon marked down from $1,449.99 to $1,099.99, which makes it the same price that the 128GB model usually sells for.

Dell G3 15 Intel Core i5-10300H 15.6-Inch 1080p Gaming Laptop w/ Nvidia GeForce GTX 1660 Ti, 16GB DDR4 RAM, 512GB NVMe SSD ($799.99)

Dell’s G3 laptops are designed to be affordable gaming computers, but they still pack a considerable punch. This laptop utilizes a Core i5 processor along with a mid-range GTX 1660 Ti graphics processor that’s able to run games at 1080p resolutions with ease. Currently you can get one marked down from $1,199.99 to$799.99 from Dell.

Western Digital Black SN750 500GB M.2 NVMe SSD ($69.99)

This WD M.2 SSD has a capacity of 500GB and it can transfer data at a rate of up to 3,430MB/s. This makes it significantly faster than a 2.5-inch SSD, and it’s also fairly inexpensive, marked down at Amazon  from $129.99 to $69.99.

Amazon Fire TV Recast Over-The-Air DVR 500GB ($129.99)

Amazon’s Fire TV Recast is a type of DVR device with 500GB of storage space that can hold up to 75 hours of video. It allows you to record up to four shows simultaneously, and this content can then be played back on a wide range of supported devices. Right now Amazon Prime members can get this device from Amazon marked down from $229.99 to $129.99.

Apple Watch Series 3 38mm w/GPS & Cellular ($169.00)

Apple’s Series 3 smartwatch is powered by a dual-core S3 processor and it features a built-in GPS as well as a cellular connection. It can also keep count of your steps and display information from your smartphone. This watch originally sold for $379.00, but you can get it today from Amazon for $169.00.

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Now read:

Understand Machine Learning and Data Analysis With The Help Of This Expert-Led Training

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Google Cloud Has a Big Edge Over AWS or Azure — and This Training Can Help You Master It

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[the-fitsquad]

Computer Repair Solutions

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Our workplace furnishings gives a vast range of metallic closets of varying sizes, distinct kinds of doors, a number of configurations of desks that will satisfy the needs of any contemporary office with lots of other accessories. Eventually, you are going to be stuck with this graphics card for the life of the laptop, so you are going to want it to be good sufficient to last through as numerous future versions of the application as feasible. The Software Licensing Service reported that this application edition does not support token-primarily based activation. six. Disputed bills account- for guests who refuse to settle their account (in part or in complete) because of a discrepancy. Here once more, HP delivers a choice of 11 various graphics cards — but this time, with assistance for up to 300 watts of graphics, the method can accommodate dual NVIDIA Quadro 6000 cards.

Fitted with a prime of the line Intel Core i7 processor and 16GB RAM, this computer makes no bones about its unprecedented efficiency. On the manufacturer’s web site, you will have the choice of deciding on the video card for the laptop. Study TRIANGLE PARK, NC – June ten, 2010: Lenovo (HKSE: 992) (ADR: LNVGY) today announced 5 new Pc goods that inject innovation back into the desktop computing space. The most widespread varieties of office workstations you will locate are linear or straight workstations, cluster or L shaped workstations, single pentagon, single seater, 4 pentagon or seater, cubicle and F3 and F2 screen systems. A contemporary lounge chair and ottoman teamed with an ergonomically created laptop pc support double the benefits of the Daybed ergonomic workstation , which can be simultaneously used as a property office workstation and piece of modern property furniture.

Our main objective is to offer you fantastic value, higher-high quality server and storage options, we recognize that every business has diverse needs and as such are able to supply un-equaled flexibility in designing custom server and storage solutions to meet our clients’ requirements. The desktop computer software application provides a very powerful stock & alternatives trading engine. The best-end Z8 characteristics 24 RAM slots and up to 3TB of RAM, dual Xeon CPUs (with up to 56 cores), dual M.2 SSDs and dual NVIDIA Quadro Pro graphics cards. Even after the warranty on your components have come to an finish, you nevertheless take pleasure in access to support and labor from Titan Computers, for life. In addition, more and a lot more folks get utilized to the new media like Web, laptop and mobile telephone without having leave the old media like tv, radio and newspaper.

The Software Licensing Service reported that the Retailer upgrade license does not enable the existing version of the installed Operating Program. Some Workstations might feature dual CPUs to improve their processing capabilities. Furthermore, Avid has chosen HP Workstations for its turnkey options, like Avid Media Composer and Avid NewsCutter items. A workstation is a specialized, single user laptop that generally has a lot more power and features than a common desktop pc. HP’s most versatile detachable to date, the HP ZBook x2 operates in 4 modes: laptop, detached, docked and tablet. Desktop is really a single of categorization in terms of Personal Computer(Computer). The method of backing up your data can be accomplished remotely by means of a file server, or locally making use of tapes, discs, DVDs, external hard drive, or the local drive.

In addition, the auditor prepares a day-to-day summary of cash, verify and credit card activities that occurred at the front desk. In conclusion workstation mobile laptops are the laptops that come with the very best and very higher-overall performance processor, graphics, memory and much much more and they use for a variety of works like animation, 3d modeling, game development, architecture works with AutoCAD, Revit and a lot much more. (Not necessarily an concern if you strategy on possessing it tucked away, although you’ll undoubtedly notice it if you engage in some of that aforementioned schlepping.) It also looks less black than it does on Apple’s internet site – far more like the “Space Gray” that it really is. As it takes place, that case is simple to unlock and slip off, on the rare occasion that you want to replace the RAM, storage or 1 of the GPUs.

The Software program Licensing Service reported that a necessary license could not be discovered. Please see slot configuration suggestions at – Note that graphics cards, Thunderbolt, and other devices will demand PCIe slots. The benefit of this desk is that the drawers is of two directional design permitting you to access numerous storages at the identical time as nicely as eliminating blind spots in the back of the drawer. One particular point that has remained unchanged with the HP Z Series Workstations is the unrivaled good quality and support provided by HP in each and every workstation. Consequently it is essential to have various designs of office desks to suit the various needs of an office. Also, there are longstanding rumors of improved iPad help across all of iOS. I feel it is safe to say that the functionality increases here are due totally to the Z820’s four additional CPU cores and new CPU architecture, not the truth that it has more RAM: none of the mental ray tests exceeded 5GB of RAM usage, and even taking Windows and other application into account, total usage stayed effectively below the 18GB of the Z800.

Filed under: General Tagged: home office desk furniture melbourne, hp workstation desktop price in india, pc workstation hp z800 from KelsusIT.com – Refurbished laptops, desktop computers , servers http://bit.ly/2C7yTeu via IFTTT

[ultragamerz]

NVIDIA TITAN V Benchmarks Leaked | This 12nm Volta GPU Is Huge

New Post has been published on https://www.ultragamerz.com/nvidia-titan-v-benchmarks-leaked-this-12nm-volta-gpu-is-huge/

NVIDIA TITAN V Benchmarks Leaked | This 12nm Volta GPU Is Huge

NVIDIA TITAN V Benchmarks Leaked | This 12nm Volta GPU Is Huge

Leaked | NVIDIA TITAN V Benchmarks | This Volta GPU Is The Strongest Ever – credit by Nvidia

Based on the leaked benchmarks the Titan V beats the Titan Xp and 1080 TI with a huge margin. This $3000 graphic card is strangely strong. A user on Reddit has assembled a collection of links to some early, unofficial benchmarks of the TITAN V. NVIDIA TITAN V Benchmarks show this Volta GPU Is the Strongest Graphic Card Ever Made In PC ever. To be safe lets call them unofficial benchmarks. TITAN V has 21.1-billion transistor GV100 GPU based on a 12nm FFN high-performance process by NVIDIA. It has 5,120 CUDA cores, 640 Tensor cores, a 1,200MHz base clock and 1,455MHz boost clock, 12GB of HBM2 memory running at 1.7Gbps, with a 3,072-bit interface for an effective 653GB/s of memory bandwidth.

Using NVIDA’s latest 388.59 WHQL drivers, the card posted a graphics score of 32,774. It does show performance numbers with the card overclocked by 170MHz, which bumped up the score to nearly 36,000 points (35,991, to be precise). To put those numbers into perspective, a TITAN Xp based on NVIDA’s Pascal GPU architecture typically scores around 28,000, as does the GeForce GTX 1080 Ti. In Unigine’s Superposition benchmark TITAN V scored 5,222 in the 8K preset, and 9,431 in the 1080p Extreme preset. GeForce GTX 1080 Ti overclocked to 2,581MHz, resulted in a score 8,642 in the 1080p Extreme preset. The TITAN V scored nearly 800 points higher.

The full specs of the Titan V is as follows: 6 Graphics Processing Clusters, 80 Streaming Multiprocessors, 5120 CUDA Cores (single precision), 320 Texture Units, 1200 MHz Base Clock  (MHz), 1455 MHz Boost Clock (MHz), 850 MHz Memory Clock, 1.7 Gbps Memory Data Rate, 4608 KL2 Cache Size, 12288 MB HBM2Total Video Memory, 3072-bit Memory Interface, 652.8 GB/s Total Memory Bandwidth, 384 Giga Texels/secTexture Rate (Bilinear), 12 nmFabrication Process, 21.1 Billion Transistor Count, 3 x Display Port, 1 x HDMI Connectors, Dual Slot Form Factor, One 6-pin, One 8-pin Power Connectors, 600 Watts Recommended Power Supply, 250 Watts Thermal Design Power (TDP), 91° C.

As we have mentioned before the Titan V is not made for gaming purposes but for fast computing, machine learning and AI Applications and Nvidia is giving the Nvidia Titan V owners free access to GPU-optimized deep learning software on NVIDIA GPU Cloud to be able to control and program the coda cores. NVIDIA TITAN V graphic card has 12 GB HBM2 memory and 640 Tensor Cores, delivering 110 TeraFLOPS of performance and a unique Volta-optimized NVIDIA CUDA: Frame Buffer 12 GB HBM2, Boost Clock 1455 MHz, Sensor Cores 640, CUDA Cores 5120. The price tag on the graphic card is $2,999 so it is not exactly for everybody and mainly not released for gaming market.  Titan V has 5120 CUDA Cores and 640 Tensor Cores and NVIDIA is saying that it is going to bring “supercomputing” is going to be available for you with this GPU architecture for your PC. This Volta-Powered GPU Delivers up to 110 Teraflops of Deep Learning Horsepower which is 9x Its Predecessor to Researchers and Scientists and data/AI proccessing. Here is the Full specs of the Monster Titan V graphic card.

Huang the Nvidia CEO said about the Titan V release in High performance computing:

“Our vision for Volta was to push the outer limits of high performance computing and AI. We broke new ground with its new processor architecture, instructions, numerical formats, memory architecture and processor links,” said Huang. “With TITAN V, we are putting Volta into the hands of researchers and scientists all over the world. I can’t wait to see their breakthrough discoveries.”

Titan V Made by Nvidia Volta For PC Finally For $3000 – Credits Nvidia

Tags: Technology, nvidia, nvidia graphic cards, nvidia volta, nvidia vlta first graphic card, nvidia volta titan v, titan v, titan v spes, titan v price, titan v release date, titan v benchmarks

[digicrunchpage]

Nvidia’s new graphics card is $3,000, painted gold, and not meant for graphics

Enlarge (credit: Nvidia)

Although Nvidia launched its 21 billion transistor Volta GPU architecture back in May, until now the chip has been used exclusively in compute cards—specifically, the Tesla V100 cards, which cost about $10,000 for the PCIe version. But now Volta GPU is available in a graphics card: at the 2017 Neural Information Processing Systems conference, Nvidia CEO Jen-Hsun Huang announced the Titan V, a $3,000 golden video card making the same GPU—the Volta architecture GV100—available to regular end users.

Unlike the Tesla cards, the Titan V is a proper graphics card. It has three DisplayPort and one HDMI outputs, it uses the standard GeForce driver stack, and it will play games. It'll probably play them quite well, although Nvidia hasn't made any gaming performance claims thus far. That's because, although it's a graphics card, it's not really being aimed at graphics applications. Rather, it's being aimed at the same kinds of GPU-based computation (especially machine learning) applications that the Tesla cards are meant for, just on a slightly smaller scale. Titan V would be used in a workstation PC, rather than a compute cluster in a datacenter.

With these similar roles in mind, it's not too surprising that Titan V's specs are extremely similar to Tesla V100's. Both cards have 5,120 compute cores, and both have 640 machine learning-oriented "tensor cores" that specialize in 4×4 matrix arithmetic. Exact clock speeds for the Tesla cards aren't known, but Titan V can boost to 1.455GHz, slightly more than V100's 1.370GHz. It's the memory subsystem that has the biggest difference: Titan V has 12GB of HBM2 memory, with a 3,072-bit memory bus. Tesla V100 has 16GB of HBM2 and a 4,096-bit bus. The Titan's memory is also a hair slower, clocked at 1.70Gb/s compared to 1.75Gb/s.

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Nvidia’s new graphics card is $3,000, painted gold, and not meant for graphics published first on http://ift.tt/2tWwSNR

[techbotic]

Nvidia’s new graphics card is $3,000, painted gold, and not meant for graphics

Enlarge (credit: Nvidia)

Although Nvidia launched its 21 billion transistor Volta GPU architecture back in May, until now the chip has been used exclusively in compute cards—specifically, the Tesla V100 cards, which cost about $10,000 for the PCIe version. But now Volta GPU is available in a graphics card: at the 2017 Neural Information Processing Systems conference, Nvidia CEO Jen-Hsun Huang announced the Titan V, a $3,000 golden video card making the same GPU—the Volta architecture GV100—available to regular end users.

Unlike the Tesla cards, the Titan V is a proper graphics card. It has three DisplayPort and one HDMI outputs, it uses the standard GeForce driver stack, and it will play games. It'll probably play them quite well, although Nvidia hasn't made any gaming performance claims thus far. That's because, although it's a graphics card, it's not really being aimed at graphics applications. Rather, it's being aimed at the same kinds of GPU-based computation (especially machine learning) applications that the Tesla cards are meant for, just on a slightly smaller scale. Titan V would be used in a workstation PC, rather than a compute cluster in a datacenter.

With these similar roles in mind, it's not too surprising that Titan V's specs are extremely similar to Tesla V100's. Both cards have 5,120 compute cores, and both have 640 machine learning-oriented "tensor cores" that specialize in 4×4 matrix arithmetic. Exact clock speeds for the Tesla cards aren't known, but Titan V can boost to 1.455GHz, slightly more than V100's 1.370GHz. It's the memory subsystem that has the biggest difference: Titan V has 12GB of HBM2 memory, with a 3,072-bit memory bus. Tesla V100 has 16GB of HBM2 and a 4,096-bit bus. The Titan's memory is also a hair slower, clocked at 1.70Gb/s compared to 1.75Gb/s.

Read 2 remaining paragraphs | Comments

Nvidia’s new graphics card is $3,000, painted gold, and not meant for graphics published first on http://ift.tt/2uzKHlW

[budgetgameruae]

Ultimate Guide to Pre Built Gaming PCs in the UAE – Powered by Budget Gamer

Gaming has become a vibrant industry, a competitive area, and a passion rather than just a pastime. Selecting the ideal Pre Built PC UAE can improve your gaming experience, regardless of your level of experience in the UAE. Our speciality at Budget Gamer is gaming PC solutions that strike a balance between cost, performance, and design.

[soorasaab]

When Nvidia launched the GeForce GTX 1080 Ti GPU last month, we were surprised to note how similar it was to the semi-professional Titan X. The 1080 Ti should have been a cut-down version of its bigger sibling, but ended up upstaging it completely thanks to the use of newer and faster components. The 1080 Ti delivered roughly the same amount of power but its price was still nearly 50 percent lower. That imbalance of course caused the Titan X to become largely irrelevant, and Nvidia has corrected this by releasing a new flagship called the Titan Xp.

This new offering will be the second Titan-level product in Nvidia's Pascal generation. The Pascal architecture has underpinned Nvidia's entire GeForce 10-series GPUs, all of which perform well and are extremely energy efficient. Interestingly, rumours of the 2016 Titan X prior to its launch last year had referred to it as "Titan XP".

This new refresh uses the same GP102 GPU, but with all of its resources fully enabled. It has 3,840 shader processor units and has a boost speed of 1582MHz. It is outfitted with 12GB of GDDR5 RAM running at 11.4Gbps on a 384-bit bus, for a total memory bandwidth of 547.7 GBps. Total pixel-pushing power is rated at 12 Teraflops, which Nvidia touts as an "irresponsible amount" of performance.

Power draw is rated at 250W and SLI HB will allow for two of these cards to be teamed up. Nvidia's spec sheet lists DisplayPort 1.4 and HDMI 2.0b connectors, indicating that DVI has been dropped just like it was on the GeForce GTX 1080 Ti Founders' Edition reference design. Cards can be used with Windows 7-10, FreeBSD and Linux workstations.

In contrast, the 2016 Titan X and the GeForce GTX 1080 Ti both have 3,584 processor units, but the latter has a slightly constrained memory pathway. The more consumer-oriented 1080 Ti also has 1GB less RAM, but it uses the same newer and faster memory chips found on the new Titan Xp. That makes this new card the best of both worlds, and clearly places it at the top of the hierarchy. It has the same $1200 (approximately Rs. 77,335) price tag that the 2016 Titan X launched at.

Nvidia Titan Xp graphics cards will be sold directly by Nvidia and as part of prebuilt systems. Official images show an all-black version of the familiar die-cast aluminium vapour chamber cooler that Nvidia has been using since the debut of the 10-series. Cards are already available for sale in the US, with availability in India unknown as of now.

Titan series graphics cards are aimed not just at gamers who demand the absolute best, but also at content creators, VR developers, and researchers working on deep learning and artificial intelligence.

In a footnote to its announcement, Nvidia also revealed that macOS support for all Pascal-based GPUs is coming later this month. The news will be welcome to those building their own "Hackintosh" machines, but could also be a hint as to what hardware and capabilities Apple's recently announced Mac Pro and iMac reinvention might have.

#SooraSaab #Soora #Facebook #News #Gadgets #Technology #sports #Automobile #blog #youtube #smartphones #top #Tumblr

[budgetgameruae]

Best PC for Data Science & AI with 12GB GPU at Budget Gamer UAE

Are you looking for a powerful yet affordable PC for Data Science, AI, and Deep Learning? Budget Gamer UAE brings you the best PC for Data Science with 12GB GPU that handles complex computations, neural networks, and big data processing without breaking the bank!

Why Do You Need a 12GB GPU for Data Science & AI?

Before diving into the build, let’s understand why a 12GB GPU is essential:

✅ Handles Large Datasets – More VRAM means smoother processing of big data. ✅ Faster Deep Learning – Train AI models efficiently with CUDA cores. ✅ Multi-Tasking – Run multiple virtual machines and experiments simultaneously. ✅ Future-Proofing – Avoid frequent upgrades with a high-capacity GPU.

Best Budget Data Science PC Build – UAE Edition

Here’s a cost-effective yet high-performance PC build tailored for AI, Machine Learning, and Data Science in the UAE.

1. Processor (CPU): AMD Ryzen 7 5800X

8 Cores / 16 Threads – Perfect for parallel processing.

3.8GHz Base Clock (4.7GHz Boost) – Speeds up data computations.

PCIe 4.0 Support – Faster data transfer for AI workloads.

2. Graphics Card (GPU): NVIDIA RTX 3060 12GB

12GB GDDR6 VRAM – Ideal for deep learning frameworks (TensorFlow, PyTorch).

CUDA Cores & RT Cores – Accelerates AI model training.

DLSS Support – Boosts performance in AI-based rendering.

3. RAM: 32GB DDR4 (3200MHz)

Smooth Multitasking – Run Jupyter Notebooks, IDEs, and virtual machines effortlessly.

Future-Expandable – Upgrade to 64GB if needed.

4. Storage: 1TB NVMe SSD + 2TB HDD

Ultra-Fast Boot & Load Times – NVMe SSD for OS and datasets.

Extra HDD Storage – Store large datasets and backups.

5. Motherboard: B550 Chipset

PCIe 4.0 Support – Maximizes GPU and SSD performance.

Great VRM Cooling – Ensures stability during long AI training sessions.

6. Power Supply (PSU): 650W 80+ Gold

Reliable & Efficient – Handles high GPU/CPU loads.

Future-Proof – Supports upgrades to more powerful GPUs.

7. Cooling: Air or Liquid Cooling

AMD Wraith Cooler (Included) – Good for moderate workloads.

Optional AIO Liquid Cooler – Better for overclocking and heavy tasks.

8. Case: Mid-Tower with Good Airflow

Multiple Fan Mounts – Keeps components cool during extended AI training.

Cable Management – Neat and efficient build.

Why Choose Budget Gamer UAE for Your Data Science PC?

✔ Custom-Built for AI & Data Science – No pre-built compromises. ✔ Competitive UAE Pricing – Best deals on high-performance parts. ✔ Expert Advice – Get guidance on the perfect build for your needs. ✔ Warranty & Support – Reliable after-sales service.

Performance Benchmarks – How Does This PC Handle AI Workloads?

TaskPerformanceTensorFlow Training2x Faster than 8GB GPUsPython Data AnalysisSmooth with 32GB RAMNeural Network TrainingHandles large models efficientlyBig Data ProcessingNVMe SSD reduces load times

FAQs – Data Science PC Build in UAE

1. Is a 12GB GPU necessary for Machine Learning?

Yes! More VRAM allows training larger models without memory errors.

2. Can I use this PC for gaming too?

Absolutely! The RTX 3060 12GB crushes 1080p/1440p gaming.

3. Should I go for Intel or AMD for Data Science?

AMD Ryzen offers better multi-core performance at a lower price.

4. How much does this PC cost in the UAE?

Approx. AED 4,500 – AED 5,500 (depends on deals & upgrades).

5. Where can I buy this PC in the UAE?

Check Budget Gamer UAE for the best custom builds!

Final Verdict – Best Budget Data Science PC in UAE

If you're into best PC for Data Science with 12GB GPU PC build from Budget Gamer UAE is the perfect balance of power and affordability. With a Ryzen 7 CPU, RTX 3060, 32GB RAM, and ultra-fast storage, it handles heavy workloads like a champ.

[lifepatrol-blog]

Subscribe and watch the video on YouTube --- https://youtu.be/9qOchEEX0C8

Alright, so you want to dive in the the data industry but you are try to swing I on a budget. You are wondering what the best computer is for data analytics. Well you came to the right place. I have done some digging and found 4 + 2 computers that will fit your needs for processing data on a budget.

If you are curious what a data analyst does, you can check out the post in the link below.

>>>> Data Analyst Job Description | Top 4 Skills Needed to become a Analyst

>>>> Top 4 Best Laptops for Data Analyst (Not on a budget)

Here at Jobs in the Future we have spent a great deal of time researching and informing you about the Data Science industry, and we will continue to do so with practical, informative content that doesn’t weigh you down with all the jargon. Today I want to touch on what gear you need to become a well outfitted Data Analyst.

On this episode of Data Gear we are going to look at the Top 4 Laptops for Data Analysts

Before any suggestions are made lets look at the key components necessary for a great Data Analystics laptop. In comparison to other industries like video editing you may not need a lot of the high tech graphics tech or editing speed, so its important to maximize the importance of other parts of the computer that will help you perform better as a Data Analyst, Scientist, or Business Analyst. Let’s look at the three main pieces to a great laptop:

1 ) Memory / RAM

Your Laptop should have at least 16GB of RAM in order to run multiple applications at the same time. You could get away with 8GB of RAM, but honestly you are already behind the tech curve if you get 8GB of RAM. Most laptobs have the option to upgrade to 32GB of RAM. If you are going to be investing in a new machine for your data analytics career you should definitely be on the cutting edge, or else you are already left behind. (it’s sad but true. Technology evolves so quickly.)

2 ) Processor

The Intel i7 processor is still the premier processor available in laptops for data analytics. You are definitely going to want to have this processor to ensure top performance for all of your data querying, scrubbing, analyzing and presenting. Could you get away with an i5, sure, but as stated in the previous point. Don’t start behind the tech curve!

3 ) Hard Drive

Don’t even think about getting anything other than an SSD (Solid State Drive). The reason being? It adds speed and readability to your computer. When you own a solid state hard drive there are ZERO moving parts. This means that there are far less opportunities to malfunction. Trust me you don’t want your computer to crash in the middle of a very important data job.

With that being said it is important to recognize that the affordable laptops for data analytics will have small SSD hard drives and a larger HDD SATA non solid state hard drive. The reason? All of your applications and software will be run on the SSD hard drive and then all of your files will be stored on the SATA. This will lower the cost on the computer, yield faster processing speeds, and give you more hard drive space.

Note: If you don’t want that large of a hard drive you could always buy an external drive by samsung to handle your data.

4 ) Graphics Processing Unit (If you are considering Data Science)

The GPU is really important, but only if you are considering getting into data science work like machine learning. When using programs like Heano, Torch, and Tensorflow they will run best on NVIDA GPUs. Don’t go for anything less than a NVIDA 960.

Note: A lot of programs and applications require you to run Linux. Fortunately for you in this day and age nearly any high level machine will handle this just fine.

What is the Best Operating System for Data Science?

Click the link to find out! Best OS for Data Science

Laptop Recommendations

Disclaimer: The first to Laptops recommended on this list on the most affordable but least powerful. I included these, though I do not FULLY recommend them as they are limited in power. Will they work? Sure. But we don’t want just the basics. We want to have a solid edge into the industry.

Base Level 1 ) Dell Inspiron i7559 5012

A solid entry level computer but missing a lot of the specs that I would be confident to give a 100% recommendation. I have included this because it is affordable, but not preferable. The reason being? No Solid State Hard drive, has a max upgrade-able ram slot of 16GB, and totes a smaller GTX 960 Graphics Card.

15.6 Inch UHD

8 GB DDR3L SDRAM, can be upgraded to 16GB

1TB 5400 rpm Hybrid Hard Drive + 8GB Embedded Flash Cache

Intel Quad Core i7-6700HQ 2.6 GHz Processor (4 Core boosts up to 3.50 GHz)

NVIDIA GeForce GTX 960M 4GB GDDR5

Base Level 2 ) MSI GL72M with 17.3″ Screen

This computer is a step up from the Dell Inspiron because it has the Nvidia GT 1050 graphics card, a 128GB solid state hard drive + 1TB of 5400rpm SATA hard drive. Unfortunately it still only has 8GB of ram, so that is a bit of a downer. We are getting better on this affordable laptop list.

Display: 17.3″ Full HD eDP Non Reflection

Processor: Intel Core i7-7700HQ (2.8-3.8GHz)

Graphics Card: NVIDIA’s GTX 1050 2G GDDR5

RAM: 8GB DDR4 2400MHz

Hard Drive: 128GB SSD + 1TB (SATA) 5400rpm

1 ) Dell Inspiron 7000 Flagship

This computer edged its way into the top 4 best affordable computers because it comes standard with 16GB of RAM, 12GB of Solid State Hard Drive + 1TB of SATA Hard Drive, but it slides in as the entry level to the top four best because of the Nvidia GTX 960 Graphics card. 16GB DDR3 RAM

Full HD 1920 x 1080

128 GB SSD + 1 TB HDD; 15.6″

NVIDIA GeForce GTX 960M 4 GB GDDR5

Intel Core i7-6700HQ Quad-Core processor, 2.6GHz can boost up to 3.5GHz

2 ) Lenovo Legion Y520

Now we are starting to develop some real power in this line up. The Legion comes with all that you need to dive in at an affordable price. RAM, 2GB of SATA Hard Drive, and the GTX 1050i. This computer is really starting to give us some hope on the affordable line up.

15.6″ FHD Anti-Glare LED Backlight

Intel Core i7-7700HQ Processor 2.8GHz (boosts up to 3.80GHz)

NVIDIA GeForce GTX 1050Ti 4GB GDDR5

16GB DDR4

256GB SSD + 2TB

3 ) Acer Predator Helios 300

The Acer Predator is a well suited computer. Lots of power and with an excellent design. The only issue I have with this computer is the small Solid State Hard Drive that is possess. I would highly recommend upgrading to a larger 512GB or 1TB Drive if you’re going to pick up this computer. Click here for Samsung! They make a great drive, or go portable external.

15.6″ Full HD (1920 x 1080) widescreen IPS display

7th Generation Intel Core i7-7700HQ Processor (Up to 3.8GHz)

NVIDIA GeForce GTX 1060 with 6 GB of dedicated GDDR5 VRAM

16GB DDR4 Memory

256GB SSD

4 ) MSI GL62MVR

The MSI GL62 is stacked with options for the price. It has all the tops specs to get you going on a budget into the data industry. MSI held back no punches getting this computer maxed out for the price. Check the specs below.

Display: 15.6″ Full HD

Processor: Core i7-7700HQ 2.8 (Boosts up to 3.8 GHz)

NVIDIA GeForce GTX 1060 6G GDDR5

RAM: 16GB (8G*2) DDR4 2400MHz (Upgrade-able to a max memory of 32GB

128GB NVMe SSD + 1TB HDD (5400RPM)

There you have it! If you are in the market for an affordable Data Analytics laptop you can select the right machine for your data needs!

Join the tribe of individuals wanting to get Motivated, Educated and Deregulated in their lives by subscribing to ourYoutube Channel! Stay up to date with all the latest tips, reviews, and education.

[ultragamerz]

Leaked | NVIDIA TITAN V Benchmarks | This Volta GPU Is The Strongest Ever

New Post has been published on https://www.ultragamerz.com/leaked-nvidia-titan-v-benchmarks-this-volta-gpu-is-the-strongest-ever/

Leaked | NVIDIA TITAN V Benchmarks | This Volta GPU Is The Strongest Ever

NVIDIA TITAN V Benchmarks | This Volta GPU Is Strongest Graphic Card Ever Made In PC

Leaked | NVIDIA TITAN V Benchmarks | This Volta GPU Is The Strongest Ever – credit by Nvidia

A user on Reddit has assembled a collection of links to some early, unofficial benchmarks of the TITAN V. NVIDIA TITAN V Benchmarks show this Volta GPU Is the Strongest Graphic Card Ever Made In PC. To be safe lets call them unoffical But hothardware also is reporting based on the same source right now. TITAN V has 21.1-billion transistor GV100 GPU based on a 12nm FFN high-performance process by NVIDIA. It has 5,120 CUDA cores, 640 Tensor cores, a 1,200MHz base clock and 1,455MHz boost clock, 12GB of HBM2 memory running at 1.7Gbps, with a 3,072-bit interface for an effective 653GB/s of memory bandwidth. Using NVIDA’s latest 388.59 WHQL drivers, the card posted a graphics score of 32,774. It does show performance numbers with the card overclocked by 170MHz, which bumped up the score to nearly 36,000 points (35,991, to be precise). To put those numbers into perspective, a TITAN Xp based on NVIDA’s Pascal GPU architecture typically scores around 28,000, as does the GeForce GTX 1080 Ti. In Unigine’s Superposition benchmark TITAN V scored 5,222 in the 8K preset, and 9,431 in the 1080p Extreme preset. GeForce GTX 1080 Ti overclocked to 2,581MHz, resulted in a score 8,642 in the 1080p Extreme preset. The TITAN V scored nearly 800 points higher.

As we have mentioned before the Titan V is not made for gaming purposes but for fast computing, machine learning and AI Applications and Nvidia is giving the Nvidia Titan V owners free access to GPU-optimized deep learning software on NVIDIA GPU Cloud to be able to control and program the coda cores. NVIDIA TITAN V graphic card has 12 GB HBM2 memory and 640 Tensor Cores, delivering 110 TeraFLOPS of performance and a unique Volta-optimized NVIDIA CUDA: Frame Buffer 12 GB HBM2, Boost Clock 1455 MHz, Sensor Cores 640, CUDA Cores 5120. The price tag on the graphic card is $2,999 so it is not exactly for everybody and mainly not released for gaming market.  Titan V has 5120 CUDA Cores and 640 Tensor Cores and NVIDIA is saying that it is going to bring “supercomputing” is going to be available for you with this GPU architecture for your PC. This Volta-Powered GPU Delivers up to 110 Teraflops of Deep Learning Horsepower which is 9x Its Predecessor to Researchers and Scientists and data/AI proccessing. Here is the Full specs of the Monster Titan V graphic card.

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Tags: Technology, nvidia, nvidia graphic cards, nvidia volta, nvidia vlta first graphic card, nvidia volta titan v, titan v, titan v spes, titan v price, titan v release date, titan v benchmarks

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6 Graphics Processing Clusters

80Streaming Multiprocessors

5120CUDA Cores (single precision)

320Texture Units

1200 MHzBase Clock (MHz)

1455 MHzBoost Clock (MHz)

850 MHzMemory Clock

1.7 GbpsMemory Data Rate

4608KL2 Cache Size

12288 MB HBM2Total Video Memory

3072-bitMemory Interface

652.8 GB/sTotal Memory Bandwidth

384 GigaTexels/secTexture Rate (Bilinear)

12 nmFabrication Process

21.1 BillionTransistor Count

3 x DisplayPort, 1 x HDMIConnectors

Dual SlotForm Factor

One 6-pin, One 8-pinPower Connectors

600 WattsRecommended Power Supply

250 WattsThermal Design Power (TDP)1

91° C

Huang the Nvidia CEO said about the Titan V release in High performance computing:

“Our vision for Volta was to push the outer limits of high performance computing and AI. We broke new ground with its new processor architecture, instructions, numerical formats, memory architecture and processor links,” said Huang. “With TITAN V, we are putting Volta into the hands of researchers and scientists all over the world. I can’t wait to see their breakthrough discoveries.”

Titan V Made by Nvidia Volta For PC Finally For $3000 – Credits Nvidia

Titan V Made by Nvidia Volta For PC Finally For $3000 – Credits Nvidia

  Tags: Technology, nvidia, nvidia graphic cards, nvidia volta, nvidia vlta first graphic card, nvidia volta titan v, titan v, titan v spes, titan v price, titan v release date, titan v benchmarks

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Nvidia’s new graphics card is $3,000, painted gold, and not meant for graphics

Enlarge (credit: Nvidia)

Although Nvidia launched its 21 billion transistor Volta GPU architecture back in May, until now the chip has been used exclusively in compute cards—specifically, the Tesla V100 cards, which cost about $10,000 for the PCIe version. But now Volta GPU is available in a graphics card: at the 2017 Neural Information Processing Systems conference, Nvidia CEO Jen-Hsun Huang announced the Titan V, a $3,000 golden video card making the same GPU—the Volta architecture GV100—available to regular end users.

Unlike the Tesla cards, the Titan V is a proper graphics card. It has three DisplayPort and one HDMI outputs, it uses the standard GeForce driver stack, and it will play games. It'll probably play them quite well, although Nvidia hasn't made any gaming performance claims thus far. That's because, although it's a graphics card, it's not really being aimed at graphics applications. Rather, it's being aimed at the same kinds of GPU-based computation (especially machine learning) applications that the Tesla cards are meant for, just on a slightly smaller scale. Titan V would be used in a workstation PC, rather than a compute cluster in a datacenter.

With these similar roles in mind, it's not too surprising that Titan V's specs are extremely similar to Tesla V100's. Both cards have 5,120 compute cores, and both have 640 machine learning-oriented "tensor cores" that specialize in 4×4 matrix arithmetic. Exact clock speeds for the Tesla cards aren't known, but Titan V can boost to 1.455GHz, slightly more than V100's 1.370GHz. It's the memory subsystem that has the biggest difference: Titan V has 12GB of HBM2 memory, with a 3,072-bit memory bus. Tesla V100 has 16GB of HBM2 and a 4,096-bit bus. The Titan's memory is also a hair slower, clocked at 1.70Gb/s compared to 1.75Gb/s.

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