spike | fast reverse proxy written in PHP that helps to expose | Proxy library

I am seeking to re-use the same role/class names in a child module as in its parent. You know, like a specialization.

The aim is to be able to re-use the same script code for both the parent and child Series variants by simply changing use Dan to use Dan::Pandas at the top.

I am trying to stick to role rather than class compostion where I can so that the behaviours can be applied to other objects with eg. class GasBill does Series;

Here is the MRE:

i have successfully done the sculpting implementation on CPU,

throw some guide on how to do this on GPU kindly …

i have moved the sculpting code to vertex shader but the sculpting is not accumulating in vertex shader and cant modify position in vertex shader… kindly tell me how …

I have a data table of 20M rows and 20 columns, to which I apply vectorized operations that return lists, themselves assigned by reference to additional columns in the data table.

The memory usage increases predictably and modestly throughout those operations, until I apply the (presumably highly efficient) frollmean() function to a column that contains lists of length 10 using an adaptive window. Running even the much smaller RepRex in R 4.1.2 on Windows 10 x64, with package data.table 1.14.2, the memory usage spikes by ~17GB when executing frollmean(), before coming back down, as seen in Windows' Task Manager (Performance tab) and measured in the Rprof memory profiling report.

I understand that frollmean() uses parallelism where possible, so I did set setDTthreads(threads = 1L) to make sure the memory spike is not an artifact of making copies of the data table for additional cores.

My question: why is frollmean() using so much memory relative to other operations, and can I avoid that?

For some reason, G1 is deciding to increase the committed old generation memory (although the used memory does not increase) and decrease the Eden generation committed memory (consequently the usable space). It seems to be causing a spike in GC's young generation runs and making the application unresponsive for some time.

We also can see a spike in CPU usage and the total committed virtual memory in the machine (which gets bigger than the total physical memory). It is also possible to see a spike in disk usage and swapout/swapin.

My questions are:

1. Is it likely that the G1 decision to decrease the Eden size and drastically increasing the old generation committed memory causing all those spikes?
2. Why is it doing that?
3. How to prevent it from doing that?

JVM version: Ubuntu, OpenJDK Runtime Environment, 11.0.11+9-Ubuntu-0ubuntu2.20.04

EDIT: Seems that what is causing the memory spike is a sudden increase in the off-heap JVM direct buffer memory pool. The image below shows the values of 4 metrics: os_committed_virtual_memory (blue), node_memory_SwapFree_bytes (red), jvm_buffer_pool_used_direct (green) and jvm_buffer_pool_used_mapped (yellow). The values are in GB.

I'm still trying to find what is using this direct buffer memory and why it has such an effect on the heap memory.

I am currently trying to crawl headlines of the news articles from https://7news.com.au/news/coronavirus-sa.

After I found all headlines are under h2 classes, I wrote following code:

I am making a figure with multiple subplots. I want each subplot to show spikes but am unable to get the spikes showing on anything other that the first subplot. I didn't see that ability to set showspikes with a fig.update_traces call. Any suggestions?

Code to reproduce:

We migrated a service from GCP App Engine to Cloud Run. This service is connected to Cloud SQL.

and its parameters are:

• max requests per container: 1
• min instances: 0
• max instances: 200

After receiving spikes, we have experienced this error multiple times:

I'm trying to use the integerChange block from the Modelica Standard library It doesn't seem to work however. What am i doing wrong? I would have expected a spike at each change,but i get a constant "false". I'm using OpenModelica 1.17

Here is the simple model

We have a webapp that uses on average 20% CPU when idle, with no network traffic or any kind of requests. It is running on Java 11, Tomcat 9, Spring Framework 5.3, Hibernate 5.4. However the issues I will describe below were true on Java 8, Tomcat 8.5, Spring 4.3 and Hibernate 4. as well. I tried to profile the application using JFR and JMC, and I experimented with a lot of configurations. In the image above it looks like catalina-utility-1 and catalina-utility-2 threads wake up periodically and for a few seconds use a lot of CPU. Also there seems to be a huge amount of memory allocations done by these threads, 30+ GB in total in the sampled 5 minutes interval.

For this profiling I've configured JFR to record everything at maximum, all options enabled.

When I tried to dig deeper into the details by looking at the Method Profiling details, I observed that it seems to be related to org.apache.catalina.webresources.Cache.getResource().

So I started to read about Tomcat caching and tried out different parameters to tune it via the context.xml file like this: