(04-10-2023 10:21 PM)Mike T. Wrote:  

(01-28-2023 09:22 AM)BINUBALL Wrote:  Tested with HP-200LX too.

Couldn't resist trying this on a modern PC...

Code:


#include <math.h>
#include <stdio.h>

void main()
{
  double i,sum;
  i=1;
  sum=0;
  for(i=1;i<=10000;i++)
  {
  sum+=pow(exp(sin(atan(i))),1/3.);
  }
  printf("%lf\n",sum);
}

$ gcc sum.c -o sum -lm
$ time ./sum 
13955.857904

real    0m0.005s
user    0m0.005s
sys    0m0.001s
$

(04-13-2023 05:14 PM)stineylee Wrote:  There are several different types of benchmarks that can be used, depending on the specific features and capabilities of the calculator in question. Summation-based benchmarks, which test a calculator's ability to perform basic arithmetic operations such as addition and subtraction, are one common type of benchmark.

Here are a few summation-based benchmarks that are commonly used to test calculators:

The "10-key" test: This benchmark measures a calculator's ability to enter and calculate a series of numbers quickly and accurately, using only the 10 numeric keys (0-9) and the basic arithmetic functions (+, -, x, ÷). In this test, the user is given a series of 10-digit numbers to enter and calculate, and the speed and accuracy of their input is measured.

The "addition stress test": This benchmark measures a calculator's ability to perform rapid-fire addition calculations without making errors. In this test, the user is given a series of simple addition problems (e.g. 1+2, 3+4, etc.) to solve as quickly as possible, with a set time limit.

The "accuracy test": This benchmark measures a calculator's ability to perform accurate calculations over a range of values. In this test, the user is given a series of increasingly complex arithmetic problems to solve, and the accuracy of their answers is compared to a known correct result.

The "decimal test": This benchmark measures a calculator's ability to handle decimal numbers accurately and consistently. In this test, the user is given a series of arithmetic problems involving decimal numbers, and the accuracy of their answers is compared to a known correct result.

The "repeated calculation test": This benchmark measures a calculator's ability to perform the same calculation repeatedly without making errors. In this test, the user is given a simple arithmetic problem to solve, and is then asked to solve it again and again as quickly as possible, without making mistakes.

(04-13-2023 05:14 PM)stineylee Wrote:  Here are a few summation-based benchmarks that are commonly used to test calculators:

(12-22-2017 09:41 PM)pier4r Wrote:  So as said the summation based test will be very similar to the savage benchmark and I wonder how many similar tests were developed on various forum or groups regarding calculators.

Anyway, inspired by the test done in the thread of Eddie linked in the 1st post, I decided to pick randomly some scientific functions to assemble a summation that may give an idea of the performances of a calculator for common math functions.

Quote:Casio fx-9860GIII, OS version 3.70.0200, MicroPython

N options:
For 100 the computation takes too little time, Result: 100.0
1000 < 1 second Result: 1000.0
10,000 3.9 seconds Result: 10000.0
100,000 62 seconds Result: 100000.0
For 1,000,000 the computation takes too much time, I skipped it

(09-10-2023 03:03 PM)toml_12953 Wrote:  Your results show
~ 18s - fx9860GIII , micropython result has reduced precision p#199

When I run the following on my fx9860GIII with OS version 3.70.0200, I get < 7 seconds.
I really wish it had an RTC. My reflexes aren't that great!

Code:

from math import *
s=0
for x in range(1,1001):
  s+=(exp(sin(atan(x))))**(1/3)
print(s)

1395.346287743426

Quote:Here are a few additional results for DB48X v0.7.1, where:

HW7 = Hardware accelerated 7 digits precision (32-bit IEEE-754)
HW16 = Hardware accelerated, 16 digits precision (64-bit IEEE-754)
VPnn = Variable precision decimal with nn digits.

...snip... would find it interesting to see that on a single implementation the value you get does not really converge depending on the underlying precision:

7 digits: 1384348,...
16 digits: 1395612,...
24 digits: 1395600,...
36 digits: 1395607,...
48 digits: 1395609,...


1 million loops:

Code:


| Version | Time (ms) | Result |
|----------------|-----------|---------------------------------------------|
| DM32 HW7 | 1748791 | 1'384'348.25 |
| DM32 HW16 | 2188113 | 1'395'612.15872'53834'6 |
| DM42 HW7 | 605102 | 1'384'348.25 |
| DM42 HW16 | 806730 | 1'395'612.15872'53834'6 |
| iPhone 12 VP48 | 1515800 | 1'395'609.35516'01878'23166'99926'37353'94572'23162'39251'9 |
| iPhone 12 VP36 | 1003884 | 1'395'607.17477'7643'16731'54275'27942'243 |
| iPhone 12 VP24 | 583237 | 1'395'600.94680'92149'84730'06 |
| iPhone 12 HW7 | 9462 | 1'384'348.25 |
| iPhone 12 HW16 | 9495 | 1'395'612.15872'53836'9 |

1000 loops on DM32/DM42:

Code:


| DM32 Version | HW7 | HW16 | VP6 | VP12 | VP24 | VP36 |
|--------------|------|------|------|-------|-------|-------|
| 0.6.4 | 1414 | 1719 | 6905 | 13720 | 32346 | 60259 |
| 0.6.2 | | | 7436 | 16017 | 34898 | 62012 |
| 0.6.0 (Note) | | | | | 23773 | |
| 0.5.2 (ID) | 2154 | | | | | |

Code:


| DM42 Version | HW7 | HW16 | VP6 | VP12 | VP24 | VP36 |
|--------------|------|------|------|-------|-------|-------|
| 0.6.4 | 422 | 705 | 5623 | 10548 | 23811 | 42363 |
| 0.6.2 | | | 5842 | 10782 | 23714 | 42269 |
| 0.6.0 (Note) | | | | | 17685 | |
| 0.5.2 (ID) | 1434 | | | | | |