cpu – Confusion in the calculation of speed for the pipeline architecture

Approach I is to calculate cycles by instruction change, regardless of the frequency increase (presumably the non-multipipe design has some risks that are not present in pipeline design, multiplexed to use multiple cycles for some instructions).

Approach II calculates the frequency increase (decrease in cycle time) from pipeline processing (ignoring overheads).

The real increase in performance, assuming a miraculous reduction in cycle times of 1.4 to 1 and pipeline steps as stupidly unbalanced (and no overhead), would be the product of both of these factors. .

If the cycle time of the uncoupled design equals the total processing time of an instruction for pipeline design, one could expect that the IPC would be the same in the circumstances ideal (no pipeline risk). In one way or another, in this example, the non-multipiled design averages more time processing an instruction than pipeline design, which indicates that it is simply accidental that times are equal; Pipeline design stages do not correspond to non-pipelined design cycle time parts.

The pipeline does not reduce the amount of work and if each pipeline stage corresponds to an equal amount of work in the unmatched design (ie, the work is not done faster), the CPI would be equal, implying that the pipeline design is not entirely pipeline. .

(Another alternative is to compare two separate ISAs, so the more pipeline friendly ISA used by the pipelined design uses 1.4 times more instructions to avoid instructions that would require more than 10 ninns to be fully processed. )

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I'm using a MacBook Pro (15-inch) with Mojave OS and BootCamp with Windows 10. I recently purchased a Thunderbolt Ethernet adapter to Gigabit. After connecting, I could select 1GB of speed and duplex when I started it as a Mac. and the speed test would indicate that I have a download speed of about 940 MB. However, if I started it in BootCamp, while the state of the internet connection indicates that I have 1 GB, the speed test would indicate that I did not have it. a download speed of 380 ~ 500 MB.

I connect it directly to my modem. In reality, the properties of the adapter under Windows do not allow to select 1 GB, but only 10/100 Mbps in full duplex / half duplex mode or auto negotiation. I have Auto for that. Some additional notes: I have a 1 Gb service plan offered by the ISP and the regular laptop of my family could also reach a speed of 900 mb once connected.

Do you have any ideas on how to get the same speed in BootCamp?

Does the operating system affect speed?

All right, before I start, I want to say that my question is different from this one. Here is my problem, I bought a desktop and tried to change the hardware of the miners to speed things up. They were expensive from elsewhere. I created this PC running Windows Server 2016 with a graphical interface. However, I installed VirtualBox in Windows 2016 to run Ubuntu at home, but it is not very slow, but it is really very slow. For example, when I click on a folder, it may take a second for that folder to be highlighted or hovered over. Would it be different if I had Windows 10 instead of Windows Server!

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If Windows Server is not the cause, what hardware do you recommend to modify or add?

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fsck – Can I speed up the first aid of the disk utility by running "fsck_hfs" with the option "-c"?

I used Disk Utility's first aid on a portable hard drive that I use for Time Machine, which took about 13 hours (no repairs needed). I was wondering if there was a way to speed up that. The release of the Disk Utility shows that it worked fsck_hfs -fy -x / dev / rdisk3and so he does not use the -c option, which according to the manual page of the command "can improve performance":

-c size Specify the size of the cache used by fsck_hfs internally.
Larger size may result in better performance, but may also result
in blocking when it is used with the -l option. The size can be specified
defined as a decimal, octal or hexadecimal number. If the
number ends with a "k", "m" or "g", the number is
multiplied by 1024 (1K), 1048576 (1M) or 1073741824 (1G),
respectively.

I was wondering if anyone had ever used the software -c option. Is fsck_hfs do not use a cache at all when the option is not used, or does it use a default size? How big would I need to set the cache size to see a significant improvement, or even some improvement in performance? I guess it depends on the size of the disk; mine is 1TB with Disk Utility showing that it contains about 15.500.000 files.

Comparative Review – Optimize code speed using C ++ instead of Python

I wrote code in python and it's like that:

import maths
import time
Itertools Import Compress


def prime_number (n):
& # 39; & # 39; & # 39; Numbers up to n & # 39; & # 39; & # 39;
sieve = ray of light ([True]) * (n // 2 + 1)
for i in the range (1, int (n ** 0.5) // 2 + 1):
if sieve[i]:
sieve[2*i*(i+1)::2*i+1] = light ray ((n // 2-2 * i * (i + 1)) // (2 * i + 1) +1)
back {2, * compresses (range (3, n, 2), sieve[1:]}} #Use to increase search time

list_of_primes = prime_number (10 ** 8) # list prime numbers up to 10 ** 8
square_numbers = {i ** 2 for i in the range (2, 10 ** 4)}
for i in square_numbers:
for j in list_of_primes:
if (j-1)% i == 0 and j in list_of_primes:
list_of_primes.remove (j)
other:
Pause

list_of_primes = list_of_primes - square_numbers
sophie_german_primes = prime_number (50 * 10 ** 6)
sg_prime = {i for i in sophie_german_primes if 2 * i + 1 in list_of_primes}

def test_condition (num):
& # 39; & # 39; & # 39; Test the condition of d + n / d by taking the input as a divider array and num & # 39; & # 39; & # 39;
for i in the range (1, int (num ** 0.5) + 1):
if num% i == 0:
if (i + num / i) is not in list_of_primes:
returns False
returns True

start = time.perf_counter ()

Sum = 0
for num in sg_prime:
if num + 2 in list_of_primes:
Sum + = 2 * num

new_list_primes = list_of_primes - {2 * i + 1 for i in sg_prime}

for num in new_list_primes:
if (num - 1) / 2 + 2 in list_of_primes:
if test_condition (num-1) == True:
Sum + = num - 1

end = time.perf_counter ()
print ("Time:", end-start, "sec")

print (Sum + 1)

The problem is that the code works. However, it works on python in 8.35 seconds. But online, I see that C ++ works much faster than python (10 to 100 times faster). Is it possible to speed up my code more than 10 times by just using C ++? Is someone ready to try this?

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