Programming, Machine Learning & Day trading PC

[Pictttureperfecttt]

Hi all - 

 

First time post & first time PC build. I have been a MacBook user in my personal life for 8 years, and use a PC for development at work. I am building a PC as my existing MacBook cannot support 4 screens, and its performance for machine learning is lackluster relative to what I am looking for. 

 

PCPartPicker Part List

CPU: AMD Ryzen 9 3900X 3.8 GHz 12-Core Processor  ($432.41 @ Amazon) 
Motherboard: Asus TUF GAMING X570-PLUS (WI-FI) ATX AM4 Motherboard  ($189.99 @ Best Buy) 
Memory: Corsair Vengeance RGB Pro 32 GB (2 x 16 GB) DDR4-3200 Memory  ($164.99 @ Best Buy) 
Storage: ADATA XPG SX8200 Pro 1 TB M.2-2280 NVME Solid State Drive  ($149.97 @ Amazon) 
Video Card: MSI GeForce RTX 2080 SUPER 8 GB GAMING X TRIO Video Card  ($818.00 @ Amazon) 
Case: Cooler Master MasterCase H500M ATX Mid Tower Case  ($239.99 @ Amazon) 
Power Supply: Corsair RMx (2018) 750 W 80+ Gold Certified Fully Modular ATX Power Supply  ($155.98 @ Newegg) 
Operating System: Microsoft Windows 10 Pro OEM 64-bit  ($139.99 @ Other World Computing) 
External Storage: Seagate Expansion 8 TB External Hard Drive  ($131.99 @ Adorama) 
Total: $2423.31
Prices include shipping, taxes, and discounts when available
Generated by PCPartPicker 2020-05-01 01:14 EDT-0400

 

1. Budget & location

$2600

United States. 

 

2. Aim. I have two requirements: 

A. PC should be able to support 4 monitors for day trading.  

B. PC should support Machine learning workload. 

 

3. Monitors.

I do have the 4 27-inch monitors, and they have HDMI & DVI ports. ASUS VE278 with 1920×1080 resolution. 

I would like a recommendation for a 4-arm stand if someone has one. 

 

4. Peripherals: 

I plan on using 64 bit Windows 10 Pro. 

Is there any other recommended software to buy on a new PC (e.g. for virus protection?) 

Already have mouse & keyboard. 

 

 

The biggest cost choices came down to CPU, GPU, and motherboard.

• While I originally was leaning with the Ryzen 3700X, I had extra budget and decided to go with 3900X since the 3800X seems like a little improvement. CPU for Machine Learning helps with some of the pre-processing of data prior to training, so I do see incremental value here. 
• I decided to go with the Asus TUF GAMING X570-PLUS (WI-FI) ATX AM4 Motherboard as it will pair with my Ryzen 3900X and seems to have good reviews overall. Have had good experience with ASUS before. 
• I have been torn between the 2080 Super vs 2080 Ti. I decided to go with the 2080 Super because for machine learning purposes, I would like to see some return on investment in regards to the work I expect to do on the machine. If I see the return on investment in my Machine Learning work, I may just spend more at a later time & get a second GPU to support my workload. 

 

One area that is particularly confusing for me is cases. I do care about the double-tempered glass with RGB light aesthetic, but with so many options and lots of variance in reviews, its hard to understand who delivers quality here. Some of the brands that seem good are Corsair, ThermalTake, and Cooler Master. Any recommendations here? The $240 for the case does seem pricey, but I think it should have good air flow. 

 

Welcome any feedback, thank you so much. This is a large investment for me. 

 

 

 

 

[igormp]

Is 8gb of vram enough for your ML models? Asking so because I'm barely cutting it with my 2060S and often need to train stuff on GCP due to the limited VRAM in consumer cards. A 2080Ti would be nice if you don't need more than 11gb, but I guess going for two 2080S and splitting your models (if possible) across both would be the best scenario.

[Pictttureperfecttt]

@Igormp, I do have access to AWS Cloud in the case that I need to train larger models at work. For my personal projects, I do not have any in development today. My ML work is not focused on computer vision, so I don't expect to have major constraints by choosing 8GB of memory for now instead of the 11GB in the Ti. 

[boggy77]

for the case, get one with a mesh front for good airflow. you shouldn't need to spend more than $150 on a good one.

I would add a cpu cooler to your list, otherwise it will be hot and loud. a bequiet dark rock pro 4 or a noctua nh-d15 are the best options. otherwise, solid  build. 

for ML, you might want to look at a 1080ti. it has almost the same gaming performance as the 2080 super, but 11gb of ram.

[Pictttureperfecttt]

37 minutes ago, boggy77 said:

for the case, get one with a mesh front for good airflow. you shouldn't need to spend more than $150 on a good one.

I would add a cpu cooler to your list, otherwise it will be hot and loud. a bequiet dark rock pro 4 or a noctua nh-d15 are the best options. otherwise, solid  build. 

for ML, you might want to look at a 1080ti. it has almost the same gaming performance as the 2080 super, but 11gb of ram.

Great, thanks for the case call out. I'm gonna go with the $104 Cooler Master that still has tempered glass on one side, but mesh net on the front for airflow. I'll look further into the 1080 Ti advice. 

 

As far as the cooler, something less hot would be ideal. Are there any RGB CPU coolers worth looking into? 

[boggy77]

25 minutes ago, Pictttureperfecttt said:

Great, thanks for the case call out. I'm gonna go with the $104 Cooler Master that still has tempered glass on one side, but mesh net on the front for airflow. I'll look further into the 1080 Ti advice. 

 

As far as the cooler, something less hot would be ideal. Are there any RGB CPU coolers worth looking into? 

get the noctua nh-d15s and add an rgb fan to it.

[igormp]

10 hours ago, boggy77 said:

for the case, get one with a mesh front for good airflow. you shouldn't need to spend more than $150 on a good one.

I would add a cpu cooler to your list, otherwise it will be hot and loud. a bequiet dark rock pro 4 or a noctua nh-d15 are the best options. otherwise, solid  build. 

for ML, you might want to look at a 1080ti. it has almost the same gaming performance as the 2080 super, but 11gb of ram.

A 2080S is way better than a 1080Ti due do the FP16 performance, since it basically nets you double performance and you can fit double the amount of data into your vram.