u/Alternative_Art2984

There are some Facebook online pages that offers to increase your score and they showed me they are working in PTE.

Is it possible? They told they will take your login details and increase scores. Is it really possible?

Hi everyone,

I’m a PhD student (in Australia) working on deep learning / video understanding, and I’ve recently got my hands on an RTX 5090 (24 GB). I’m not building this system for gaming at all purely for research workloads (training models, large datasets, possibly multi-GPU in the future).

I’m trying to figure out the rest of the setup, but most recommendations online are very gaming-focused, which isn’t really helpful for my use case.

Right now I’m unsure about:

• CPU choice (should I go high core count like Ryzen 9 / Threadripper, or something else?)
• Motherboard (reliability + PCIe lanes matter more than RGB or gaming features)
• RAM (capacity vs speed — is 64GB enough or should I go 128GB?)
• Storage (best setup for fast dataset loading — NVMe vs multiple drives?)
• PSU and cooling (for long training runs, stability is key)

My priorities are:

• Stability during long training jobs
• Fast data loading / preprocessing
• Scalability for future upgrades (maybe more GPUs later)
• No unnecessary “gaming” features

Budget is flexible but I don’t want to waste money on things that don’t actually improve research performance.

Hi everyone,

I’m a PhD student (in Australia) working on deep learning / video understanding, and I’ve recently got my hands on an RTX 4090 (24 GB). I’m not building this system for gaming at all purely for research workloads (training models, large datasets, possibly multi-GPU in the future).

I’m trying to figure out the rest of the setup, but most recommendations online are very gaming-focused, which isn’t really helpful for my use case.

Right now I’m unsure about:

• CPU choice (should I go high core count like Ryzen 9 / Threadripper, or something else?)
• Motherboard (reliability + PCIe lanes matter more than RGB or gaming features)
• RAM (capacity vs speed — is 64GB enough or should I go 128GB?)
• Storage (best setup for fast dataset loading — NVMe vs multiple drives?)
• PSU and cooling (for long training runs, stability is key)

My priorities are:

• Stability during long training jobs
• Fast data loading / preprocessing
• Scalability for future upgrades (maybe more GPUs later)
• No unnecessary “gaming” features

Budget is flexible but I don’t want to waste money on things that don’t actually improve research performance.