New ask Hacker News story: Ask HN: Worth it to buy 4x Nvidia Tesla K40 for AI?
Ask HN: Worth it to buy 4x Nvidia Tesla K40 for AI?
9 by speedylight | 3 comments on Hacker News.
I saw a post on a local market place that’s selling a complete system with 4 Tesla K40s 12 GBs VRAM w/ passive cooling for $400. The post description said that the system was intended to be used for training AI models, which is what I want to use it for… nothing too serious I am mostly still learning here. The cards themselves were released on 2013 and would have a combined cuda cores of 12,928 if I’m counting the 5th video card for a monitor (GTX 1660) Here are the complete specs from the post description… from a dollar value of all these parts, I’m not really losing any money… I just don’t have good enough intuition to see if this system is worth it to learn practice modern day AI. Specs: Motherboard: MSI MAG Z390 Tomahawk gaming 9th generation with dual Ethernet ports for wiring with other servers, and max speed 4400 MHz in overclock mode. CPU: Intel Core i5-9400f @4.10 GHz x 6 cores (overclock mode). RAM: 64 GB (4x16) DDR4 max speed 3600 MHz. Storage: One m.2 NVMe SSD 256 GB (for operating system) + Two 3 TB Hard Disk Drive (for data storage) Gaming Display Support: 1 GTX 1660 Super graphic card with 6 GB memory and 1,408 cuda cores, supporting max 3 monitors at the same time. Bus max transfer speed 8.0 GB/s (gen3 mode). AI Deep Learning: 4 Tesla K40 AI accelerators each with 12 GB memory and 2,880 cuda cores, dedicating to machine or deep learning, Bus max transfer speed 8.0 GB/s (gen3 mode) each. Power supply safety: One 700 W PSU dedicated to the motherboard and the GTX 1660 monitor GPU. Another 1,000 W PSU dedicated to the Tesla K40 AI accelerators. CPU Cooling: Cooler Master liquid cooler with LED light control. AI Accelerator Cooling: 4 cooling fans at front and 3 cooling fans at back. Structure: Open frame of high strength Al alloy to safeguard your system in an intensive working environment. Power switch: Big button switch with 5 ft flexible extension cable, and LED indicator for hard drive.
9 by speedylight | 3 comments on Hacker News.
I saw a post on a local market place that’s selling a complete system with 4 Tesla K40s 12 GBs VRAM w/ passive cooling for $400. The post description said that the system was intended to be used for training AI models, which is what I want to use it for… nothing too serious I am mostly still learning here. The cards themselves were released on 2013 and would have a combined cuda cores of 12,928 if I’m counting the 5th video card for a monitor (GTX 1660) Here are the complete specs from the post description… from a dollar value of all these parts, I’m not really losing any money… I just don’t have good enough intuition to see if this system is worth it to learn practice modern day AI. Specs: Motherboard: MSI MAG Z390 Tomahawk gaming 9th generation with dual Ethernet ports for wiring with other servers, and max speed 4400 MHz in overclock mode. CPU: Intel Core i5-9400f @4.10 GHz x 6 cores (overclock mode). RAM: 64 GB (4x16) DDR4 max speed 3600 MHz. Storage: One m.2 NVMe SSD 256 GB (for operating system) + Two 3 TB Hard Disk Drive (for data storage) Gaming Display Support: 1 GTX 1660 Super graphic card with 6 GB memory and 1,408 cuda cores, supporting max 3 monitors at the same time. Bus max transfer speed 8.0 GB/s (gen3 mode). AI Deep Learning: 4 Tesla K40 AI accelerators each with 12 GB memory and 2,880 cuda cores, dedicating to machine or deep learning, Bus max transfer speed 8.0 GB/s (gen3 mode) each. Power supply safety: One 700 W PSU dedicated to the motherboard and the GTX 1660 monitor GPU. Another 1,000 W PSU dedicated to the Tesla K40 AI accelerators. CPU Cooling: Cooler Master liquid cooler with LED light control. AI Accelerator Cooling: 4 cooling fans at front and 3 cooling fans at back. Structure: Open frame of high strength Al alloy to safeguard your system in an intensive working environment. Power switch: Big button switch with 5 ft flexible extension cable, and LED indicator for hard drive.
Comments
Post a Comment