If you want to improve your productivity, you should first identify the bottleneck in your system. The bottleneck is the part of your system that limits your ability to perform at peak performance. It can be a resource, or it could be an application process.
There are several ways to find out where the bottleneck is in your system.
One way is to use the “bottleneck analysis tool” provided by Google. It allows you to see where your system spends its time. You can also use the “Time Profiler” feature in Visual Studio to analyze your code and determine where the bottlenecks are.
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Once you have identified which parts of your system are causing problems for you, there are two approaches you can take:
1) If you know what causes the problem, then try to fix it.
For example, if you suspect that memory leaks cause slowdowns, then you need to figure out how to prevent them from happening. This may involve changing your design so as not to create new objects unnecessarily, or perhaps even rewriting.
A bottleneck occurs when one component of your system takes up too much CPU time. A good analogy would be traffic on a highway.
When all lanes become congested, cars start backing up behind each other until they reach their destination. In this case, the bottleneck is the road itself.
The same thing happens with computers. Your computer has many components such as processors, RAM, hard drives, etc., but only some of these components actually do useful work. These components are called resources. Resources include things like CPUs, disk space, network bandwidth, and more. You can build online using computer system
Only certain combinations of resources will allow your computer to run efficiently. For efficient system build make sure to take help from online pc builder.
When we talk about a bottleneck being caused by a particular resource, we mean that the resource is taking up most of the available computing power. We call this situation a high-load scenario because the amount of load placed upon the resource is very large compared to the capacity of the resource.
To understand why a bottleneck exists, let’s look at our car analogy again. Imagine that you’re driving down the freeway and suddenly realize that every lane is backed up.
Now imagine that you’ve got three lanes going toward your destination, and another three lanes coming back. That means that nine people are trying to get into your vehicle while only four seats are available. Clearly, something needs to change!
In software systems, the equivalent of having multiple lanes heading towards your destination is using lots of different threads.
Each thread represents a separate task that must be completed before the next step can begin. To make matters worse, sometimes tasks overlap.
So instead of just 9 people wanting to enter your car, now you might have 18 people waiting to get inside.
And since no matter how fast you drive, you’ll never be able to accommodate everyone who wants to ride along, you end up getting stuck in traffic.
In short, a bottleneck is any place in your program where you cannot keep up with demand.
One technique used to identify bottlenecks is The Five Why Method. It was developed by Toyota Motor Corporation, and involves asking questions to help find root causes of an issue. Here’s how it works:
This question helps us narrow down the scope of the problem.
Was it due to user error?
Did someone else use my code incorrectly?
Or maybe the bug occurred during testing. Whatever the reason, narrowing down the scope makes finding the solution easier.
Now we know what happened, so we need to figure out why it happened. This question forces us to think outside the box. Maybe there were problems with the hardware or operating environment. Perhaps the application wasn’t designed correctly. If nothing obvious comes to mind, then we should ask ourselves if anything changed recently.
Once we’ve identified the cause, we want to determine whether they are common issues. For example, perhaps all users encounter similar errors when performing specific actions. In other cases, however, one person may see a problem while others don’t. When this occurs, we need to dig deeper to discover which conditions lead to the problem occurring for each individual.
If we still haven’t found the answer after five whys, then we need to go further.
What happens when the same thing happens over and over again?
Is there some kind of pattern emerging from these incidents?
Are certain types of events more likely than others?
These are important considerations as we try to prevent future occurrences.
Finally, once we’ve determined the underlying reasons behind the problem, we need to consider possible solutions. How could we fix things? Could we improve on the current design? Can we add new features? We also need to take note of potential side effects. Does changing one part of the system affect other parts? Will adding additional resources solve the problem? Only through careful consideration will we arrive at effective solutions.
To start identifying your biggest bottlenecks, first look at the most time-consuming operations within your app. You’re probably familiar with them already – those long running processes that seem to eat up all available CPU cycles.
But do you really understand their impact on performance?
Do you know exactly how much longer they’d run without being interrupted?
Or even better yet, do you know how many times per second they actually execute?
The good news is that you can easily measure the execution frequency of any process using PerfMon or iostat. To get started, open the Performance Monitor or System Activity Viewer, right click on the Processes tab and select “New Column…”. Then enter the name of the process into the Name column and its PID number into the ID column. Finally, set the Frequency field to be displayed in seconds instead of milliseconds.
Next, let’s examine another type of operation: those that require lots of memory.
The reason I’m focusing on RAM here is because it’s often overlooked by developers who focus only on processor usage.
But just like processors, memory has an upper limit beyond which it cannot grow indefinitely.
As soon as the amount of free space reaches that point, applications begin experiencing slowdowns due to thrashing.
This means that every time data needs to be stored somewhere else, the application must perform disk accesses to find out where to store it.
If the storage medium isn’t fast enough, the entire computer slows down until the next write completes.
So what should you look for?
First off, check the size of the working set. A large working set indicates that the program is constantly accessing different areas of memory.
Now let’s turn our attention to a third category of resource consumption: network bandwidth.
Network traffic consists of packets sent between two endpoints. The rate at which this occurs depends on several factors including packet sizes, transmission rates, etc. But regardless of the specifics, each packet requires processing overhead before it can be transmitted across the wire. This includes parsing headers, verifying checksums, encrypting payloads, etc. In addition to these overheads, there are also delays associated with sending and receiving messages. These include queuing, buffering, scheduling, routing, etc.
All told, if you have a lot of small packets coming from multiple sources, then you’ll likely experience high latency when trying to send/receive them. And since latency directly impacts response time, you may see poor user experiences.
Fortunately, measuring network throughput is easy. Just use Wireshark to capture traffic while performing some activity such as browsing the web. Once captured, analyze the resulting trace file to determine the average round trip delay. If it takes more than 10ms to complete one request, then you’ve got a problem!
What about other resources?
There are plenty of others besides RAM, CPUs, and networks that contribute to overall performance. For example, hard drives and SSDs consume power and generate heat. They’re not cheap either so they need to be cooled properly.
Also keep in mind that many modern operating systems will cache frequently used files locally rather than reading them from disks all the time. So even though the OS might think that the drive is idle, it could still be busy writing cached copies back to the local machine.
Once you know what’s causing the slowdown, how do you fix it? Well, first things first – make sure everything works correctly. Then start looking into ways to improve performance. Here are three common approaches:
1) Reduce CPU load
2) Increase available RAM
3) Improve networking speed
The best way to avoid bottlenecks is by avoiding them altogether. That said, sometimes we just don’t have control over certain aspects of an app or website. When that happens, try to reduce their impact as much as possible. You can always add additional hardware later but doing so now won’t help anything.
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