If there are many branch mispredictions and the number of branch mispredictions is not increased much by sharing the branch target buffer and branch history table between two threads.
Then one thread can use all the execution resources while the other thread is waiting for the misprediction to be resolved. If the code has many long dependency chains that prevent efficient use of the execution units. In these cases, each of the two threads will run at more than half speed, but less than full speed.
The total performance is never doubled by hyperthreading, but it may be increased by e. On the other hand, if the performance is limited by any of the shared resources, for example the instruction fetcher, the memory read port, or the multiply unit, then the total performance is not increased by hyperthreading.
Actually, in the worst cases the total performance is decreased by hyperthreading because some resources are wasted when the two threads compete for the same resources. A quick google search reveals several examples of applications that run slower with hyperthreading than when hyperthreading is disabled.
I have tested two microprocessors with hyperthreading: the Intel Core i7 and the Intel Atom. The Core i7 has four cores. This processor is quite powerful.
The execution units of each core are so powerful that a single thread will rarely utilize the full potential of the processor. Therefore, it makes good sense to run two threads in the same core.
Unfortunately, the instruction fetch unit is less powerful, and this is likely to be a bottleneck even in single-threaded applications. With hyperthreading enabled, the Core i7 can run eight threads simultaneously. This can give an impressive performance in favorable cases, but how many applications are able to keep eight threads busy at the same time?
The Intel Atom is a small low-power processor which is used in small netbook computers and embedded applications. It has two cores capable of running two threads each. The execution units of the Atom are much smaller than the i7. It sounds like a weird idea to share the already meager execution units between two threads. The rationale is that the Atom lacks the out-of-order capabilities of the bigger processors.
When the execution unit is waiting for an uncached memory operand or some other long-latency event, it would have nothing else to do in the meantime unless there was a second thread it could work on. The details of these processors are explained in my microarchitecture manual www. Obviously, it can be quite difficult for a software programmer to predict whether hyperthreading is good or bad for a particular application.
The only safe way of answering this question is to test it. So, one of the solutions was to put more than one CPU in every processor, so that the various jobs could be divided between them. Today, quad-core CPUs are pretty much the mainstream configuration. It basically means that one CPU core can work on two problems at the same time. Just that it can ensure all its capacity is used by dealing with multiple simpler problems at once.
To your operating system, each real silicon CPU core looks like two, so it feeds each one work as if they were separate. This is another question that can be a little complicated but is actually pretty simple when you break it down. Given that they are close to each other in single-thread, single core performance.
Because the quad-core CPU has more physical processing hardware. Now our question really has to do with the software that you want to run. Simply because none of the processing capacity is being wasted and the component is working near its full potential as much of the time as possible. Traditionally operations such as CPU 3D rendering, video encoding, and photo manipulation will create as many threads as your poor CPU can take.
In other words, many modern professional applications are thread-hungry. This is why Hyperthreading has been restricted to professional-tier CPUs such as the i7 and up.
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