ram | premiere open-source | Application Framework library

I try to run my React Native project on MacBook Pro M1 but when I run adb it's gives error : zsh: segmentation fault adb.

I tried run adb from both ~/Library/Android/sdk/platform-tools & ~/usr/local/bin/adb.

Tried reinstall platform-tools in android studio.

Tried install and reinstall platform-tools from brew.

Tried reinstall android studio itself.

Device: MacBook Pro M1 2020, SSD: 512, RAM: 8

OS: macOS Monterey

Android Studio: android-studio-2021.1.1.21-mac_arm

I feel like there is probably a better way to do this in tidyverse than a for-loop. Start with a standard tibble/dataframe, and make a list where the name of the list elements are the unique values of one column (group_by?) and the list elements are all the values of another column.

My computer uses a CPT of Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz 2.59 GHz. Also my RAM memory size is 16 GB. When I run the following panel VAR model "pvargmm" in R,

First, the question: is there a way to choose the platform (e.g. x86_64, AMD64, ARM64) for a GitHub Codespace?

Here's what I've found so far:

Attempt 1 (not working):

From within GitHub.com, you can choose the "machine" for a Codespace, but the only options are RAM and disk size.

Attempt 2 (EDIT: not working): devcontainer.json

When you create a Codespace, you can specify options by creating a top-level .devcontainer folder with two files: devcontainer.json and Dockerfile

Here you can customize runtimes, installed packages, etc., but the docs don't say anything about determining architecture...

...however, the VSCode docs for devcontainer.json has a runArgs option, which "accepts Docker CLI arguments"...

and the Docker CLI docs on --platform say you should be able to pass --platform linux/amd64 or --platform linux/arm64, but...

When I tried this, the Codespace would just hang, never finishing building.

Attempt 3 (in progress): specify in Dockerfile

This route seems the most promising, but it's all new to me (containerization, codespaces, docker). It's possible that Attempts 2 and 3 work in conjunction with one another. At this point, though, there are too many new moving pieces, and I need outside help.

1. Does GitHub Codespaces support this?
2. Would you pass it in the Dockerfile or devcontainer.json? How?
3. How would you verify this, anyway? [Solved: dpkg --print-architecture or uname -a]
4. For Windows, presumably you'd need a license (I didn't see anything on GitHub about pre-licensed codespaces) -- but that might be out of scope for the question.

References:
https://code.visualstudio.com/docs/remote/devcontainerjson-reference
https://docs.docker.com/engine/reference/commandline/run/
https://docs.docker.com/engine/reference/builder/
https://docs.docker.com/desktop/multi-arch/
https://docs.docker.com/buildx/working-with-buildx/

I can't recall if I have ever tinkered with the settings of Android Emulator, but I've been testing my app on an Android Emulator using Android Studio, and every time I take a screenshot, it crashes.

I tried deleting, and wiping, and creating a new Emulator. None of it works. I tried also to take a screenshot without running my app, with a fresh emulator, and the same problem occurs. It just crashes whenever I try to take a picture.

Android Studio reports this error:

Blockquote WARNING | unexpected system image feature string, emulator might not function correctly, please try updating the emulator. WARNING | cannot add library /Users/sbenati/Library/Android/sdk/emulator/qemu/darwin-x86_64/lib64/vulkan/libvulkan.dylib: failed INFO | configAndStartRenderer: setting vsync to 60 hz INFO | added library /Users/sbenati/Library/Android/sdk/emulator/lib64/vulkan/libvulkan.dylib WARNING | cannot add library /Users/sbenati/Library/Android/sdk/emulator/qemu/darwin-x86_64/lib64/vulkan/libMoltenVK.dylib: failed INFO | added library /Users/sbenati/Library/Android/sdk/emulator/lib64/vulkan/libMoltenVK.dylib INFO | Started GRPC server at 127.0.0.1:8554, security: Local INFO | Advertising in: /Users/sbenati/Library/Caches/TemporaryItems/avd/running/pid_935.ini

My machine is a Mac with 32GB of RAM and i7 CPU, so I can't imaging this an issue with system performance.

If no one has any suggestions, I will have to just reinstall everything. Thanks for the tips everyone.

Edit:

I ran this on a new Mac mini I recently acquired, and got this really helpful message. I traced it down to a suggested solution about switching off Vulcan, but it did not work for me.

I have an API that recently started receiving more traffic, about 1.5x. That also lead to a doubling in the latency:

This surprised me since I had setup autoscaling of both nodes and pods as well as GKE internal loadbalancing.

My external API passes the request to an internal server which uses a lot of CPU. And looking at my VM instances it seems like all of the traffic got sent to one of my two VM instances (a.k.a. Kubernetes nodes):

With loadbalancing I would have expected the CPU usage to be more evenly divided between the nodes.

Looking at my deployment there is one pod on the first node:

And two pods on the second node:

My service config:

We use App Buddy as our CI/CD system. Today we migrate project from ASP.NET Core 3.1 to NET 5. After that dotnet build start consuming a lot of RAM (allocate about 10-12GB) and we dont have as much memory on our server.

On our CI/CD server during dotnet build we get Microsoft.CSharp.Core.targets(71,5): error : Process terminated. System.OutOfMemoryException: Exception of type 'System.OutOfMemoryException' was thrown.

I've tried use -maxCpuCount:1 but it doesn't work. Is it any possibility to limit memory which dotnet build can use?

According to the answers in this question, std::vector implements "special" logic (to allow each boolean value to be stored in a single bit, rather than taking up an entire byte), and because of that, it doesn't quite fulfil the requirements of an STL container and its use is therefore discouraged. However, the "special" logic is retained for backward-compatibility reasons.

My question is, if the C++ implementers were to throw out the "special" logic and turn std::vector into just another specialization of the std::vector template, what backwards compatibility problems would that cause? i.e. is there some special behavior that old software might be relying on that requires the bit-packing implementation to be retained? (the only thing I can think of is that some old software in a RAM-constrained environment might be relying on the eightfold-reduction in memory usage in order to function, but that seems like a relatively minor concern in most contexts)

I have a LinkedList class which contains and automatically inserts nodes in the correct order. Note this is a linked list data structure (the array in which the nodes/elements are kept represents RAM, and the pointers - head, tail, as well as next and prev represent addresses in RAM (but in this example, they are indexes of the array in which the nodes are kept).

Eg