Sign in to vote. Monday, July 6, PM. Hi, As I know there is no official tool for monitoring CPU temperature, so seems that only third party software could achieve your desire.
Tuesday, July 7, AM. Thanks for your response, but none of them works in WS Tuesday, July 7, PM. Hi, Thank you for your feedback. Wednesday, July 8, AM. Wednesday, July 8, PM. Thanks for your response, but as I mentioned in my last post, I don't see any information about CPU Temperature in this app. How can I see CPU core temperature using this app or any other app or application?
Monday, July 13, PM. As an illustration, here are several examples of LaunchAgents related to mainstream Mac infections: com. To begin with, the web browser settings taken over by the virus exploiting WindowServer process should be restored to their default values.
Although this will clear most of your customizations, web surfing history, and all temporary data stored by websites, the malicious interference should be terminated likewise. The overview of the steps for completing this procedure is as follows:. The Mac maintenance and security app called Combo Cleaner is a one-stop tool to detect and remove WindowServer virus.
This technique has substantial benefits over manual cleanup, because the utility gets hourly virus definition updates and can accurately spot even the newest Mac infections. Furthermore, the automatic solution will find the core files of the malware deep down the system structure, which might otherwise be a challenge to locate.
Download Combo Cleaner. By downloading any applications recommended on this website you agree to our Terms and Conditions and Privacy Policy. The free scanner checks whether your Mac is infected.
To get rid of malware, you need to purchase the Premium version of Combo Cleaner. Despite a good deal of negative feedback from users, WindowServer is a legitimate macOS process that plays an important role in enabling proper manifestation of graphical elements on the display.
It is geared toward dynamic reflection of app windows and the embedded visual objects so that the user experience is seamless. In some situations, though, WindowServer may get out of hand by gobbling up most of the processor and memory resources. This likelihood of this drag increases when a user connects an external display to their Mac, especially one that supports 4K resolution.
The problem may also be security-flavored: crudely made malware, crypto miners, and adware often impersonate benign system services and are to blame for slowing down a system to a crawl. It depends on the root cause of the problem.
In this scenario, try restarting your computer and see how it goes. Be sure to apply the latest macOS update, too. The guide above will point you in the right direction. Under adverse circumstances like that, this maintenance instrument automatically takes on an active role in curbing CPU-intensive processes to reduce the heat.
Identifying the main reason for a slowdown will provide actionable insights into what area of the system needs fine-tuning in the first place. For instance, if too many apps are launched at startup, you should audit the list and eliminate redundant items. Scenarios vary, but the following tips help address most system productivity issues:. The former stores short-term data your apps require to run seamlessly, and the latter is the total storage capacity of your hard disk HDD or SSD.
P-states define the clock frequencies and voltage levels the processor supports. T-states do not directly change the clock frequency, but can lower the effective clock speed by skipping processing activity on some fraction of clock ticks.
Together, the current P- and T- states determine the effective operating frequency of the processor. Lower frequencies correspond to lower performance and lower power consumption.
Time that is spent in high-performance states versus low-performance states significantly affects energy use and battery life. All user-mode programs in Windows run in the context of a process. A process includes the following attributes and components:. Although processes contain the program modules, context and environment, they are not directly scheduled to run on a processor.
Instead, threads that are owned by a process are scheduled to run on a processor. A thread maintains execution context information. Almost all computation is managed as part of a thread. Thread activity fundamentally affects measurements and system performance. Because the number of processors in a system is limited, all threads cannot be run at the same time.
Windows implements processor time-sharing, which allows a thread to run for a period of time before the processor switches to another thread.
The act of switching between threads is called a context-switch and it is performed by a Windows component called the dispatcher. The dispatcher makes thread scheduling decisions based on priority , ideal processor and affinity , quantum , and state. Priority is a key factor in how the dispatcher selects which thread to run. Thread priority is an integer from 0 to If a thread is executable and has a higher priority than a currently running thread, the lower-priority thread is immediately preempted and the higher-priority thread is context-switched in.
When a thread is running or is ready to run, no lower-priority threads can run unless there are enough processors to run both threads at the same time, or unless the higher-priority thread is restricted to run on only a subset of available processors. Each thread has an ideal processor that is set either by the program or automatically by Windows. Windows uses a round-robin methodology so that an approximately equal number of threads in each process are assigned to each processor.
When possible, Windows schedules a thread to run on its ideal processor; however, the thread can occasionally run on other processors. The program sets affinity by using SetThreadAffinityMask. Affinity can prevent threads from ever running on particular processors. Context switches are expensive operations. Windows generally allows each thread to run for a period of time that is called a quantum before it switches to another thread.
Quantum duration is designed to preserve apparent system responsiveness. It maximizes throughput by minimizing the overhead of context switching. Quantum durations can vary between clients and servers. Quantum durations are typically longer on a server to maximize throughput at the expense of apparent responsiveness.
On client computers, Windows assigns shorter quantums overall, but provides a longer quantum to the thread associated with the current foreground window.
Each thread exists in a particular execution state at any given time. Windows uses three states that are relevant to performance; these are: Running , Ready , and Waiting.
Threads that are currently being executed are in the Running state. Threads that can execute but are currently not running are in the Ready state. Threads that cannot run because they are waiting for a particular event are in the Waiting state. A running thread or kernel operation readies a thread in the Waiting state for example, SetEvent or timer expiration. If a processor is idle or if the readied thread has a higher priority than a currently running thread, the readied thread can switch directly to the Running state.
Otherwise, it is put into the Ready state. A thread in the Ready state is scheduled for processing by the dispatcher when a running thread waits, yields Sleep 0 , or reaches the end of its quantum.
A thread in the Running state is switched out and placed into the Ready state by the dispatcher when it is preempted by a higher priority thread, yields Sleep 0 , or when its quantum ends. A thread that exists in the Waiting state does not necessarily indicate a performance problem. Most threads spend significant time in the Waiting state, which allows processors to enter idle states and save energy. Thread state becomes an important factor in performance only when a user is waiting for a thread to complete an operation.
In addition to processing threads, processors respond to notifications from hardware devices such as network cards or timers. When a hardware device requires processor attention, it generates an interrupt. Windows responds to a hardware interrupt by suspending a currently running thread and executing the ISR that is associated with the interrupt. During the time that it is executing an ISR, a processor can be prevented from handling any other activity, including other interrupts.
For this reason, ISRs must complete quickly or system performance can degrade. To decrease execution time, ISRs commonly schedule DPCs to perform work that must be done in response to an interrupt.
For each logical processor, Windows maintains a queue of scheduled DPCs. DPCs take priority over threads at any priority level. Before a processor returns to processing threads, it executes all of the DPCs in its queue. This property can lead to problems for threads that must perform work at a certain throughput or with precise timing, such as a thread that plays audio or video.
If the processor time that is used to execute DPCs and ISRs prevents these threads from receiving sufficient processing time, the thread might not achieve its required throughput or complete its work items on time. The Windows ADK writes hardware information and assessments to assessments results files. Because Windows supports symmetric multiprocessing systems only, all information in this section applies to all installed CPUs and cores.
This graph always contains data on the Target idle state for each processor. Each row in the following table describes an idle state change for either the Target or Actual state of a processor.
The following columns are available for each row in the graph:. Each state has a separate row in the timeline. Each row in the following table represents time at a particular frequency level for a processor. The Frequency MHz column contains a limited number of frequencies that correspond to the P-states and T-states that are supported by the processor.
The default profile defines the Frequency by CPU preset for this graph. In most traces, this is one millisecond 1ms. Each row in the table represents a single sample. The weight of the sample represents the significance of that sample, relative to other samples.
The weight is equal to the timestamp of the current sample minus the timestamp of the previous sample. The weight is not always exactly equal to the sampling interval because of fluctuations in system state and activity. Any CPU activity that occurs between samples is not recorded by this sampling method. Weight is expressed as a percentage of total CPU time that is spent over the currently visible time range. The number of samples represented by a row.
This number includes samples that are taken when a processor is idle. For individual rows, this column is always 1.
The number of samples represented by a row, excluding samples that are taken when a processor is idle. For individual rows, this column is always 1 or 0, for cases when the CPU was in a low power state. The time in milliseconds that is represented by the sample that is, the time since the last sample. CPU Usage grouped by thread priority shows how high-priority threads impact lower-priority threads. CPU Usage that is grouped by process shows the relative usage of processes. In this sample graph, one process is shown to be consuming more CPU time than the other processes.
CPU Usage that is grouped by process and then grouped by thread shows the relative usage of processes and the threads in each process. The threads of a single process are selected in this graph. Each row represents a set of data that is associated with a single context switch; that is, when a thread started running. Data is collected for the following event sequence:. Labels for Timestamp columns display at the top of the diagram, and labels for Interval Duration columns display at the bottom of the diagram.
These timelines can overlap as long as the order of the numbered events is not modified. For example, the Readying Thread can run on Processor-2 at the same time that a new thread is switched out and then back in on Processor New thread , which is the thread that was switched in. It is the primary focus of this row in the graph. Old thread , which is the thread that was switched out when the new thread was switched in.
The CPU usage of the new thread after it is switched. This value is expressed as a percentage of total CPU time over the currently visible time period. The number of context switches that are represented by the row. This is always 1 for individual rows. The number of waits that are represented by the row. This is always 1 for individual rows except when a thread is switched to an idle state; in this case, it is set to 0.
The CPU usage of the new thread after the context switch. This is equal to the NewInSwitchTime, but is displayed in milliseconds. The previous CState of the processor. If this is not 0 Active , the processor was in an idle state before the new thread was context-switched in.
CPU Usage on a per-process, per-thread timeline, shows which processes had threads running at certain times. This graph identifies bursts of high-priority thread activity at each priority level.
In this graph, CPU usage is grouped first by process and then by thread. It shows the relative usage of processes and the threads in each process Figure 15 CPU Usage Precise Utilization by Process, Thread shows this distribution across multiple processes:. Data is collected at the start and end of fragments. A row for each fragment is displayed in the data table. Duration fragmented that is expressed as a percentage of total CPU time over the currently visible time period.
Exclusive duration that is expressed as a percentage of total CPU time over the currently visible time period. Inclusive duration that is expressed as a percentage of total CPU time over the currently visible time period. They are graphed as a timeline. Stack trees portray the call stacks that are associated with multiple events over a period of time. Each node in the tree represents a stack segment that is shared by a subset of the events.
The tree is constructed from the individual stacks and is shown in Figure 20 Stacks from Three Events:. Figure 22 Tree Built from Stacks shows how the common segments are combined to form the nodes of a tree:. In assessment-reported issues, the tree is displayed together with the aggregate weights. Some branches can be removed from the graph if their weights do not meet a specified threshold. The sample stack below shows how the events represented above are displayed as part of an assessment-reported issue.
That duration is called the exclusive time spent in the function. For example, Function1 calls Function2. Function2 spent 2ms in a CPU-intensive loop and called another function that ran for 4ms.
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