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  1. Hello Guys, I need your help, your suggestions. Recently I was having a very hard time training my models on a non GPU Laptop I have to upgrade and I am not able to find a single laptop with Rtx 2070 or above available in India under budget. Training on cloud is also too expensive for me and I have got no choices left. I don't know what should I do building a pc will not be an efficient option as I am a student and I spend most of my year on campus. Even If I get a laptop with a thunderbolt3 port I will not be able to get a gpu enclosure for it (none available here). I don't know what I should do. Please guys let me know what I should do. Thank You.
  2. I was asked to prepare parts list for Machine Learning PC with budget of $1200 (roughly, real budget is 5000PLN which is bit over $1300 but prices in Poland may vary from US). So, here is part list of the build that I prepared: Main requirement was dual GPU for Computer Vision ML applications but with that budget I moved to single GPU with option to upgrade later down the line. But still couldn't go too high and I have chosen RTX 2060. Other parts are meant to stay as they are but still provide ways to upgrade (hence 850W PSU). So there are 2 slots for more RAM left, enough power for second GPU even along with more powerful CPU. Went for fast AF main storage M.2 NVMe SSD with 500GB to keep currently used data sets and 2TB HDD for long time storage of those. If there is something wrong, any overkill part, compatibility issues: please let me know. If there is anyone that does ML and has any advice feel free to roast me, I think advice would be most appreciated regarding GPU choice (keep in mind target dual GPU setup).
  3. Hey all! I'd love an opinion on something. For a few years now i've been mainly using a MacBook pro (currently i7 6 cores, 16GB ram, radeon 560x) and lately i've been considering adding a more powerful desktop to my rig and since I have no intention whatsoever on shelling out for an iMac pro/mac pro i've been seriously considering getting a windows/linux desktop system instead. The Aim for the system is mainly for work (coding/machine learning/unity and other computational intensive tasks) but probably also some gaming. As for monitors, for the time being i'll probably use my existing dual dell US27 1440p displays and i'm all set with peripherals. Budget (I adjusted for price differences): 2500$ US prices Lastly, i'll probably hold off any purchase till I see how everything unfolds with Zen3/RTX super etc... so you can take that under consideration Upgrade reason: There's a limit to what a laptop can do compared to a desktop. Main question: Is it possible to build a system that will answer the needs written above and also being an mini itx system which will be thermally stable (not throttling) and quiet? If so, what do you recommend? Thanks in advance for your advice, Pizza.
  4. Hello! I am looking forward to buying a PC for machine learning. I am going to use 4 cards of RTX 2080. I think about getting the Threadripper 2950x, will it do the job with it (without bottlenecking?) and Will the corsair 750D be good enough to hold them (without them overheating too much?) etc. This was my general idea, please give feedback: CPU: Threadripper 2950x GPUs: x4 RTX 2080 RAM: 64GB ddr4 MotherBoard: Gigabyte Designare SSD: samsung 500GB 970 EVO m.2 NVMe Case: corsair Obsidian Series® 750D PSU: corsair 1600w water cooling: enermax Liqtech-TR4 II 360mm Thanks for helping!
  5. Hi! Im looking to buy a cpu for a pc that will use 4 gpus of RTX 2080. These are the options I came up with. which one should I take (or a different cpu): Intel: Amd: i9-7940x Threadripper 2950x i9-7960x i9-7980xe
  6. I am just starting to learn about neural networks using Tensorflow.js. Does anyone have any idea for a simple dataset I could use for a regression problem?
  7. Hey everyone, I am currently running an AMD FX8350 on a ASRock 990FX extrem 3 Mainboard and now facing a few issues while getting my K80 to work as a secondary GPU for handling ML workloads. Sadly i can not get BAR 64 (above 4G encoding) enabled on my mainboard, therefore i am currently looking for a cheap replacement. Are there any other search phrases besides "above 4G decoding" or "BAR 64bit" that i can search for in the mainboards datasheets? Or does anyone know how a AM3+ based Mainboard with two PCIE 16x slots, K80 support and BAR 64 option? My current setup is really bodgy 2 PSUs, one for each GPU, and a custom 3D printed fan setup for the K80. Was really fun to set it up, even though it feels kind of dirty Best regards Langhalsdino
  8. I am going to university next year and I wanted to build a PC to take with me, one that can game but also do some machine learning and computing related tasks as I am applying to Computer Science. Also do some very light editing of videos and photos. I have the following part list: AMD Ryzen 7 2700X GIGABYTE AORUS B450 I PRO MSI RTX 2070 AERO ITX Corsair Vengeance LPX Black 32GB DDR4 3200MHz CL16 Dual Channel Kit 512 GB ADATA SX6000 M.2 SSD Seagate Barracuda Guardian 4TB Hard Drive Corsair SF600, 80+ Gold, 600W Velka 5 Case Any thoughts?
  9. Hello world, I have recently created a website that allows people to buy, share and sell machine learning datasets and models. Please do check out the website below if you have a dataset or model you'd like to share. Any form of feedback is truly appreciated. https://mindlabs.zone
  10. I have an app that I'm developing that I want to accelerate the machine learning aspect of. I've done CUDA programming before, but that was on my personal desktop and I'm trying to migrate the app to a different system entirely. I already have the machine for the app set up, all except for the GPU. Currently it's using it's iGPU for display, but I still want an Nvidia card for acceleration. I was looking at the wiki page for comparing GPU gFLOPS, but this is really the only metric I can see that's comparable for ML applications. Anyone know what I should try going for? Should I be trying to get some RTX card to get Tensor Cores? Do Tensor Cores truly make a difference for ML apps?
  11. Hi. Thanks to a few recommendations and some research from different places (especially here (thanks!)), I managed to squeeze the 1400$ budget and get a much better build from it. Keep in mind that I intend to upgrade this into a 2x 1070ti within the next year and a half, when trying to figure out why I went with this motherboard and PSU. Any recommendations/comments are welcome. What modifications would you recommend if you had an additional 100$ to spare on this build? I will wait for the Ryzen 3000 series to come out before buying the CPU. PCPartPicker part list / Price breakdown by merchant Type Item Price CPU AMD - Ryzen 5 2600 3.4 GHz 6-Core Processor $164.89 @ OutletPC Thermal Compound Arctic Silver - 5 High-Density Polysynthetic Silver 3.5 g Thermal Paste $6.58 @ OutletPC Motherboard Gigabyte - X470 AORUS ULTRA GAMING ATX AM4 Motherboard $143.88 @ OutletPC Memory G.Skill - Ripjaws V Series 32 GB (2 x 16 GB) DDR4-3200 Memory $234.99 @ Newegg Storage Silicon Power - S55 480 GB 2.5" Solid State Drive $54.89 @ OutletPC Storage Seagate - Barracuda 2 TB 3.5" 7200RPM Internal Hard Drive $59.89 @ OutletPC Video Card EVGA - GeForce GTX 1070 Ti 8 GB GAMING Video Card $364.98 @ Newegg Case NZXT - Phantom 530 (Red) ATX Full Tower Case $99.99 Power Supply EVGA - BQ 750 W 80+ Bronze Certified Semi-Modular ATX Power Supply $49.99 @ B&H Case Fan Thermaltake - CL-F011-PL12BL-A 40.99 CFM 120mm Fan $5.49 @ SuperBiiz Case Fan Thermaltake - CL-F011-PL12BL-A 40.99 CFM 120mm Fan $5.49 @ SuperBiiz Prices include shipping, taxes, rebates, and discounts Total (before mail-in rebates) $1241.06 Mail-in rebates -$50.00 Total $1191.06 Generated by PCPartPicker 2019-01-06 02:12 EST-0500 Can´t believe I didn´t end up pasting the link last time
  12. Hi. I would like your opinion on the differences in performance of different types of DL algorithms this build I put together on pcpartpicker.com, can achieve? PCPartPicker part list / Price breakdown by merchant Type Item Price CPU AMD - Ryzen 5 2600 3.4 GHz 6-Core Processor $164.99 @ Amazon Motherboard Gigabyte - X470 AORUS ULTRA GAMING ATX AM4 Motherboard $143.88 @ OutletPC Memory G.Skill - Aegis 16 GB (1 x 16 GB) DDR4-2400 Memory $94.99 @ Newegg Memory Corsair - Vengeance LPX 8 GB (1 x 8 GB) DDR4-2400 Memory $54.99 @ Amazon Storage Kingston - A400 240 GB 2.5" Solid State Drive $36.00 @ Amazon Storage Seagate - Barracuda 2 TB 3.5" 7200RPM Internal Hard Drive $59.89 @ OutletPC Video Card NVIDIA - GeForce GTX 1070 Ti 8 GB Founders Edition Video Card $599.00 @ Amazon Power Supply EVGA - BQ 750 W 80+ Bronze Certified Semi-Modular ATX Power Supply $49.99 @ B&H Prices include shipping, taxes, rebates, and discounts Total (before mail-in rebates) $1243.73 Mail-in rebates -$40.00 Total $1203.73 Generated by PCPartPicker 2019-01-05 08:07 EST-0500 I know the 750W PSU looks like overkill, but I intend to upgrade the CPU in the future (if I believe I will get enough of a percentage boost on the performance) and to add either another 1070ti (the board supports SLI) or maybe even eventually upgrade it to two 1080ti´s... How would you improve upon these the most given that the budget is 1400$* for the build and case, which is missing because I haven't found one that 1 - is under 100$, 2 - offers good air flow and 3 - has decent aesthetics - I welcome suggestions in that regard as well. About the GPU... What is the difference in performance between the NVIDEA 1070ti - https://pcpartpicker.com/product/4ZrmP6/nvidia-geforce-gtx-1070-ti-8gb-founders-edition-video-card-900-1g411-2510-000 for 599$ and the Zotac 1070ti - https://pcpartpicker.com/…/zotac-geforce-gtx-1070-ti-8gb-am… - for 429.99$ . The Price difference is considerable, and they both seem to have the same number of CUDA cores (2432). How great would the difference in performance be? So many questions... you need not answer them all. Just speak your mind in whichever question/s you would like to answer. Assume I will buy all parts new when considering ways to add more bang to the 1400$ budget. Thanks
  13. Hello i am planning a workstation build on a fairly limited budget, about 1100 dollars to be precise. It will be used for machine learning, compiling programs and general thinkering I'm a hobbyist when it comes to Machine learning, currently i am designing my own network, and tinkering with other networks on GitHub. but there is a slight problem. my current main computer, an asus ux360ua with integrated graphics anda corei7 6500U, does not like when i test algorithms on it. so i decided it was time for an upgrade and i wonder, what problems could i run into with this build: https://pcpartpicker.com/list/Vr3Dhy surely some bottle necking must occur when pairing a 300 dollar cpu and 200 dollar mobo with a 100 dollar gpu? will it be severe enough to cause a problems? let me know many thanks
  14. So, I'm in the market for a GPU specifically for machine learning, and it's going into a headless server, so I really do not care about 3D gaming as far as this rig goes. I need at least CUDA 3 compatibility (obviously the higher the better), the higher memory and processor power also helps. But I'm unsure of which one to get, and what kind of spending I could expect. Honestly I think my limit is about $250 USD, but if I need to go higher, I can wait a little bit and save what I need. Any help is appreciated.
  15. So. I've been researching and following AI/ML for some time now and have been following up some courses online. I'm going to be joining college in a month or so. Now i have my parents permision to buy titan v because i will not be able to afford future upgrades, so this will be it. I wll be squeezing every last bit of investment i'm putting into this. My budget is $3700 ... so. heres what i understand. -RAM, GPU and Storage is Crucial. RAM - https://www.ebay.com/itm/Corsair-Dominator-Platinum-Series-32GB-4-x-8GB-DDR4-2666-PC4-21300-2666MHz-C16/283036773409?epid=691261448&hash=item41e64e6c21%3Ag%3AgWIAAOSwVXZbOj9K&_sacat=0&_nkw=Corsair’s+Dominator+Platinum&_from=R40&rt=nc&LH_TitleDesc=0 1. Atleast double the memory of the GPU (titan v has 12) so 32gb 2- Secondhand because ram unlike CPU, GPU and Motherboard does not degrade a lot in performance from overclocking. 3- Clock speed does not need to be crazy because most current cpus only have limited system memory I'm probably wrong about system memory.Correct me please. 4. Also Intel will soon be releasing a Optane persistant memory. what are your thoughts on that? Will it preserve my work if the power goes out (I live in India. so this will happen very often). What are your thoughts on use of server memory like Load Reduced DIMM. 5. Talkingabout server memory some Current CPUs support ECC memory. I've read on some other forums that ECC is not a big concern for beginners but for a well trained model ECC is a must. so Later maybe? CPU- This one I'm most Conflicted about.... Intel or Ryzen? ... more cores or more GHz?... ECC or non ECC? This one has to be solved in Comments i guess. GPU- Titan V (single) The heart of my build. I chose this Despite of AMD's upcoming 7nm Vega Instinct because CUDA is more popular than steam cores. AMD might gain traction in this department soon because of their open source platform. I don't care about the leaked 32gb hbm2 or 20TFLOPS of speed. It will probably be another Accelerator card or a very expensive replacement for quadro GV100... not for me Radeon instinct MI25 was a excellent competitor to titan XP but they went and made it a accelerator card. Their marketing and engineering department is like a troubled marriage with excellent children. Seriously! you make the best deep learning oriented GPU... WITH hbm2, BEFORE nvidia and still be behind in that race. I can also earn from rendering other peoples work from some cousin of mine who works at an architecture firm startup. I can partner with them when i can learn how to render using ray tracing and explore the house in VR.... Far fetched plan but good plan. this will be state of the art in my city. titan v is actually cheaper on EBAY for only $2600 but im too paranoid to buy from there. STORAGE- SSD good HDD bottleneck... Optane Better...SDD Okay... but Optane is good with HDD so. - Optane SD 900P 280 gb with a good high memory HDD will be good. I need help here with the hard disk types and if there are any new ones oriented toward this purpose. PSU and Peripherals- One perk about TITAN V is that the Computer need not run for days. so long runs are not a problem. Neither am i going fancy with RGBs and Peripherals. Only CPU will be Chilled and i cannot afford GPU cooling. im not sure i the RAM needs cooling, and the optane has a heatsink of its own. The Case will probably have to be open case and will be operated with the AC and fan running in the room. There is no monitor because i have a LG 4K 60Hz Smart TV. probably the one Linus has at his test bench. The computer will be at home for safety purposes and will be remotely controlled by me from another city. yeah and thats it. I'll install Ubuntu 18 as the OS and Windows 10 (pirate4evr)
  16. TLDR: Have a £3k budget for an analysis machine, need hardware recommendations. Hello, I'm a complete novice when it comes to building but I thought I would give myself a challenge. I'm based in the UK and have just secured a fairly hefty research grant with a decent budget set aside for hardware. I reckon after buying a few neuro specific pieces of tech I'll have £3000 left for an analysis PC. The PC will be used to perform computational neuroscience analyses which includes machine learning, AI development, spectral analysis and quite meaty image analysis of MRI scans. As I say, I don't know much about PC hardware so I thought you guys might help me with choosing the CPU and GPU and maybe explain why you're recommending? Thanks very much! P.S. first time posting so apologies if I've not followed the rules in some way.
  17. Any suggestions which laptop to use for machine learning and data science at affordable price.
  18. Hey everyone, I am still in planning phase before I order parts for my new PC. I will be using this pc for mostly machine learning research hence my will be working mostly on Linux (Ubuntu Distro). Also I will be gaming on it a little bit. I am very confused and not able to decide which cpu to get. The decision has been made on the following config, Graphics Card : Asus ROG Strix GTX 1080 Ti 2 Tb Hard Disk 7200 rpm 500 Tb SSD 512 Gb Samsung 970 Pro M.2 32 Gb Ram I am confused as to which CPU to get. I will be adding another GPU as my models and data get bigger, but will not exceed two GPUs. I don't want to have bottlenecking because of the number of pcie lanes available with the cpu and also don't want to pay through the nose for a i9 processor. I don't know much about pcie lanes and how many do I need. I just know that I need to run the GPUs at 16x. If someone could explain that also, it would be great. Does anyone have suggestions or advice regarding what cpu to get or even if this config is ok for the task of machine learning. Thanks in advance.
  19. I saw a post recently about using OpenAI Universe and Gym to teach a self driving car in GTA V. Other articles say you can train AI to run Fold It. Could someone make a guide on how to do this. It would be amazing if I could run it on my pc when not in use to make generations of AI that hopefully get better at folding.
  20. Hi all, I might sound like I don’t how to google stuff like this but that’s the case here. I spent hours doing my research and still can’t figure out the best setup. Threadripper 1950x or i9 7900x? Ryzen 7 1700x\1800x or i7 8700k? Motherboards is just whole nother story. Full linux compatibility / decent iommu groups. I’m lost guys. I’m looking for a good “under $4000” Machine learning / passthrough / gaming setup (gaming is least important). Thanks
  21. Hey guys, I am going to build a machine learning focused build, for my studies in university. Maybe going to have a budget of 100,000 PHP (1300 - 1800 USD). Right now this is the build I have planned: https://pcpartpicker.com/list/h8BccY CPU: Ryzen 7 1800x CPU Cooler: Noctua NH-D15 Mobo: Asus Crosshairs Hero (Wifi-AC) RAM: G-Skill Ripjaws (2 x 16) 32 GB Storage (boot): 500 GB Samsung 960 Evo Storage (Mass): 2, 2TB WD Black in RAID1 GPU: Titan XP PSU: Corsair AX760 Case: Phanteks Enthoo Pro M Please note that: I will primarily use Tensorflow and Scikit-Learn Libraries. I am relatively new to PC building, and machine learning. The Titan XP will be lent to me by the university not bought. So, I would gladly accept any advice to make my rig better. Also, please say if there are any incompatibilities with my hardware choices, so I can make the appropriate modifications. Any recommendations will be greatly appreciated. Again, I am relatively new to pc building and hardware, so please be nice. Thank you for your response.
  22. Hi, We are planning to build a new rig for our research group. It would be used for Machine Learning/ Deep Learning projects. We deal with text, image, and video data. We want our system to have 4 Nvidia GTX1080Ti. No SLI, so multiple students can use it at a time(one student can use 1 GPU). Apart from this, we want to have RAM - 64 GB (we may increase it to 128GB if we would have budget left after getting everything else) A 512GB SSD for OS and current project. A 4TB HDD for long-term storage What CPU and Motherboard do you guys suggest for optimal performance? How many PCIe lanes my CPU should support so it does not become a bottleneck for my GPUs? Do we need a dual CPU setup or a single CPU would do the job? Anything else we should keep in mind while building this rig? Additional information:- 1. Budget & Location We are from INDIA and have a budget of 5,00,000 INR. 2. Aim Machine Learning/ Deep Learning projects 3. Monitors and Peripherals No monitors and peripherals, it would be a remote access rig. 4.OS Ubuntu Thank you
  23. Hello there! I want to build a slightly future proof build for my deep learning projects. Some of the specs that I am considering now are: ASUS Z10PE-D8 WS INTEL XEON E5 2620 V4 (only 1 for now) GTX 1080ti (2 way sli). Also, don't know which is better? founder edition or aib? like EVGA's etc. Help me in building the compelete rig for deep learning projects. Tell me please if I am thinking in a correct way for a future proof rig? Thanks in advance.
  24. Primary Source: Nature Biomedical Engineering Secondary Source: 9to5 Google This are the times that I have a profound appreciation of technology especially if it's used to save people's lives just like how an Apple Watch saved a man from heart attack. But before anyone jumps that this is the pseudomedical practice of "Iridology" where a medical charlatan uses patterns in the eyes to diagnose systemic health problems and later prescribe snake oil supplements, this is not one of those. Rather, Google trained their machine learning algorithms by looking into Opthalmoscopy results of 300,000 people and specifically look at the retinal fundus. The researchers used the standard model libraries and scripts in Tensor Flow. It's kinda like when genetic testing center 23andMe offered tests for $100 to look for genetic predispositions of certain diseases like heart disease and cancer until the US FDA shut it down because people are freaking out and making medical decisions based on that which actually makes sense because just because someone with a genetic predisposition to a certain illness doesn't mean they'll have it. There are women with BRCA1 mutation and yet they live their lives normally and don't get a cancer diagnosis. With this one, it looks at pictures inside the eye and they achieved 70% accuracy compared that to a standard basic metabolic panel which achieves 72%. Once Google perfected this, it can become a standard tool for diagnosis and prevention. While most overweight and obese individuals are still at a higher risk for Type 2 Diabetes and Hypertension, there are now people suffering from heart problems despite presenting no physical risk factors. One advantage of this is that it's less expensive and it's not invasive. You don't need to be exposed to radiation for a coronary calcium CT scan to detect calcified plaques (atherosclerosis) within the coronary arteries. But this is not yet final as it need to be compared against existing diagnostic procedures like a 2D Echocardiogram which can detect structural abnormalities in the heart or an angiogram which can diagnose diseases related to blood vessels. But since it can also predict diabetic outcomes, it may as well serve as a diagnostic tool to replace the cumbersome fasting requirements to test glucose tolerance or treat metabolic syndrome earlier before complications get worse.
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