mathijs727

Open task manager and check memory usage while using Blender

Upgrading to 2 sticks of the same brand/model/size and installing them in the correct RAM slots on your motherboard will make your ram faster (dual channel => more bandwidth). Memory capacity will not make your computer go faster unless you were running out of memory in the first place. If you buy a RTX3080 then you should also buy a new power supply (600W is not enough). Nvidia recommends 750W or more: https://www.thefpsreview.com/2020/09/03/nvidia-reiterates-750-w-psu-requirement-for-geforce-rtx-3090-and-geforce-rtx-3080/.

Unless you are running out of memory, adding more RAM will not make Blender run faster (more bandwidth / lower latency will).

I’m not sure why it’s this slow but you should not expect 3000MB/s writes. According to their marketing material, the drive should be able to write at 1050MB/s. The 3000MB/s write number is for the 4TB model (see attachment; image taken from Amazon.com).

It was probably stuck at some lower clock speed. I had this issue before with an Intel processor and the Intel XTU (overclocking) software. Because of some bug it decided to heavily downclock the CPU cache reducing system performance.

A RX5500 is about the same speed as a RX590

Maybe you could install a separate instance of Windows 10 to your HDD (create a small partition to install it to). Then copy the files in the WindowsApps folder from the new installation to the old installation.

What I'm saying is that it has the bandwidth and devices might support it, BUT it is not officially part of the specification.

According to the HDMI spec website, HDMI 1.4b is limited to 120hz at 1920x1080(so anything above is out of spec): https://www.hdmi.org/spec/hdmi1_4b

I think HDMI 1.4 can only do 144Hz at 1920x1080 not 2560x1080. Following the logic in the top rated post of this Reddit topic the theoretical maximum frame rate is 98Hz (272e6 / (2560 * 1080)).

I'm currently running the RM550x with a GTX1080 (and AMD 3900X CPU) and it's fine. Except for extreme overclocking you should not be running into any issues. I did check with a power meter once and it showed like 250W of total system power usage so I'm not worried at all.

Bought a 2 year old Volkswagen High Up! to drive to work everyday. I don't need a larger/faster car since I'm traveling alone anyways. Just wish Volkswagen would have put a small turbo in it to boost performance (advertised as 60HP but more like 20/25HP at normal RPMs) and to improve the fuel economy on the highway. The fuel usage goes up quite dramatically over 90 kph which means I tend to stick behind lorries, which is quite relaxing actually.

Since this is for professional use you should look at professional hardware. Both AMD as well as Nvidia sell hardware specifically for this use case. Not only do those cards support way more displays per card, they also come with extra features such as unifying all displays into one virtual monitor and bezel correction: https://www.nvidia.com/en-us/design-visualization/solutions/nvidia-mosaic-technology/ https://www.amd.com/en/technologies/eyefinity-professionals With some Displayport hubs it might be possible to connect 9 displays to a single GPU (if it supports 9 displays - consumer cards are usually limited to 3 or 4): https://www.club-3d.com/en/detail/2409/multi_stream_transport_(amst)_hub_displayportt_1.2_triple_monitor/

If I were you I would just contact Asus directly and ask what the exact problem could be and whether it can be fixed with a future bios update. Also, running 3 GPUs on a low-end board is kinda weird already, especially 3 mid-range graphics cards (instead of 1 or 2 high-end ones).

Looking at the manual (page 9 / ix), I think it is expected for the second slot to run in PCIe-3 4x mode: https://dlcdnets.asus.com/pub/ASUS/mb/SocketAM4/ROG_STRIX_B450_F_GAMING/E14401_ROG_STRIX_B450-F_GAMING_UM_WEB.pdf The 3rd slot is running of the motherboard chipset at PCIe-2 4x speeds. I assume that with the 3900x (which introduced a lot of changes with respect to I/O) running a GPU over the chipset (on this motherboard?) is broken.

His answer is: no your motherboard and CPU are not damaged. Overclocked RAM (which this is) not working (in all slots) is expected behavior.

Im running a 3900X + GTX1080 on a 550W PSU without issues (although I admit that 550W might be stretching it a bit), 750W is more than enough. EDIT: CPU package power is ~145W max (without PBO) in Cinebench R20. GPU power maxed out at 160W in CS:GO although it might get a bit higher in more GPU intensive games (rated at 180W). So even a 550W PSU is well within spec for such a setup.

I think they just changed the line-up to only include higher wattage units, combined with a new white color scheme: https://www.corsair.com/eu/en/Categories/Products/Power-Supply-Units/c/Cor_Products_PowerSupply_Units?q=%3Afeatured%3ApsuPowerEfficiency%3AGold%3ApsuLinkSupport%3ANo&text=#rotatingText

RTX does not use octrees, it uses Bounding Volume Hierarchies (BVH) which have been the most popular acceleration structure in ray tracing for years. For simple scenes the BVH is a tree hence ray traversal = tree traversal. However when instancing comes into play a BVH node can have multiple parents so it turns into a DAG structure. Also, GPUs have been outperforming (similarly priced) CPUs for years so I wouldn't call it something recent (before RTX GPUs were already much faster). Ray traversal also requires back tracking (most commonly using a traversal stack) so that's not an argument. The only real difference between ray tracing and maybe some other graph traversal applications is the amount of computation that has to be done at each visited node (ray / bounding box intersections in the case of ray tracing). And graph traversal itself isn't that branch heavy either. You basically have the same operation (visiting a node) repeated in a while loop. Sure, selecting the next child node contains some branches but those are one-liners. For example in the case of ray tracing: if left child is closer than push right child to the stack first, otherwise push left child first. Computing which child is closest (and whether it is hit at all) is computationally intensive and not very branch heavy. A bigger issue with ray tracing is the lack of memory coherency which reduces the practical memory bandwidth on the GPU (having to load a cache line for each thread + the ith thread not always accessing the i*4th byte in a cache line). Nvidia themselves also promote their GPUs as being much faster at graph analysis than CPUs: https://devblogs.nvidia.com/gpus-graph-predictive-analytics/

GPUs can still be faster for graph algorithms. In a sense, ray tracing is also a graph traversal algorithm (directed acyclic graph) and GPUs do pretty well there (compared to similarly priced CPUs).

Did you compare the prices in combination with a X570 motherboard or a B450/X470 mobo? Buying a 3700X with a X570 makes little sense (cheap CPU with expensive mobo) unless you really need the added features (PCI-E 4). Look into B450/X470 motherboards that support flashing the bios without a CPU (none of the current stock of motherbaords will have an up-to-date bios), should be much cheaper than a 9900K.

Here is how a C++ implementation would look like: #include <algorithm> #include <vector> #include <iostream> void alteringFunction(std::vector<int>& v) { // Add number (42) to the array v.push_back(42); // Sort array std::sort(std::begin(v), std::end(v)); // No need to return since we modified the vector in-place } int main() { std::vector<int> data { 5, 8, 1, 3, 4 }; alteringFunction(data); // Print output for (int v : data) std::cout << v << std::endl; } Note that C++ comes with a vector container that can dynamically grow (or shrink) unlike C. It also ships with a set of useful algorithms including sort, which is much faster than bubble sort for larger arrays (required to have O(N log N) average case time complexity).

In C, you could just pass a pointer to the start of the array + a number representing the size of the array. In C++ you can store the data in a std::array and pass a reference to that array. Adding to the array won’t be possible since it is fixed size (although you could add a dummy value when creating the array). In C++ you can also use a std::vector instead, which does support growing (and shrinking) dynamically. I don’t know about C, but sorting in C++ is easy: std::sort(std::begin(vector), std::end(vector));

I’m not sure how you installed python & pip but it seems like pip is not in your path. Ensure that the Python scripts folder is in your path (https://projects.raspberrypi.org/en/projects/using-pip-on-windows) Alternatively, just reinstall Python and make sure to check the “set PATH for all users” checkbox.

You need to run this from the command line: python -m pip install redis Or: pip install redis Also, don't store your commands in a bash file but just open command prompt and manually enter and execute them (then it will show you the error without immediately closing).