|
Simbody
3.5
|
These functions provide access to the system's high resolution interval timer, and highest precision sleep facility for unscheduling a thread until it is needed at a specific later time. More...
Functions | |
| long long | SimTK::realTimeInNs () |
| Return current time on the high-resolution interval timer in nanoseconds, as a 64-bit integer count. More... | |
| double | SimTK::realTime () |
| Return current time on the high-resolution interval timer in seconds. More... | |
| void | SimTK::sleepInNs (const long long &ns) |
| Sleep for the indicated number of nanoseconds, with the actual precision system dependent but intended to be the best achievable, hopefully less than 5ms in all cases. More... | |
| void | SimTK::sleepInSec (const double &seconds) |
| Sleep for the indicated number of seconds, with the actual precision system dependent but intended to be the best achievable, hopefully less than 5ms in all cases. More... | |
These functions provide access to the system's high resolution interval timer, and highest precision sleep facility for unscheduling a thread until it is needed at a specific later time.
The interval timer measures elapsed time from some arbitrary starting point (typically since the system was last booted). It is expected that this timer provides very precise measurement of short time intervals, but cannot be depended upon to measure very long periods without drifting. That is, it may not be synchronized to the system time of day.
Generally it is most convenient to measure intervals as a floating point number of seconds, however this provides a variable amount of precision as the absolute value of the timer increases. For maximum precision, you can obtain the timer value as an integer number of nanoseconds instead. You can improve accuracy by subtacting the integer counts first before converting to seconds. The actual resolution is system-dependent, but it should be able to accurately measure elapsed times of 1ms or less, substantially less on some systems.
|
inline |
Return current time on the high-resolution interval timer in nanoseconds, as a 64-bit integer count.
Generally it is more convenient to use realTime() which reports the interval time in seconds instead, but the nanosecond count is best for maximum accuracy and consistency.
|
inline |
Return current time on the high-resolution interval timer in seconds.
For maximum precision, you can improve repeatability and accuracy somewhat by obtaining the interval times as integer counts using realTimeInNs().
|
inline |
Sleep for the indicated number of nanoseconds, with the actual precision system dependent but intended to be the best achievable, hopefully less than 5ms in all cases.
However, when this wakes up you should not assume you reached the desired time; you could wake up a little earlier or a lot later. Alternatives to this are SimTK's sleepInSec() function, or the Posix nanosleep() and usleep() functions.
|
inline |
Sleep for the indicated number of seconds, with the actual precision system dependent but intended to be the best achievable, hopefully less than 5ms in all cases.
However, when this wakes up you should not assume you reached the desired time; you could wake up a little earlier or a lot later. Alternatives to this are the SimTK sleepInNs() function, or the Posix nanosleep() and usleep() functions.


| Elements' Summary |
| ScanLines |
Number of scanlines for this bitmap.
This value must not be negative
|
| ScanLineBytes |
Number of data bytes per scanline.
This value must not be negative
|
| ScanLineStride |
Byte offset between the start of two consecutive scanlines.
This value is permitted to be negative, denoting a bitmap
whose content is flipped at the x axis.
|
| PlaneStride |
Byte offset between the start of two consecutive planes.
This value is permitted to be negative. If this value is zero,
the bitmap is assumed to be in chunky format, otherwise it is
assumed to be planar. The difference between chunky and
planar layout lies in the way how color channels are
interleaved. For a chunky format, all channel data for a
single pixel lies consecutively in memory. For a planar
layout, the first channel of all pixel is stored consecutive,
followed by the second channel, and so forth. |
| ColorSpace |
Color space the bitmap colors shall be interpreted within. |
| Palette |
This member determines whether the bitmap data are actually
indices into a color map. |
| IsMsbFirst |
This member determines the bit order (only relevant if a pixel
uses less than 8 bits, of course). |
| Elements' Details |
ScanLines
long ScanLines;
- Description
- Number of scanlines for this bitmap.
This value must not be negative
|
|
ScanLineBytes
long ScanLineBytes;
- Description
- Number of data bytes per scanline.
This value must not be negative
|
|
ScanLineStride
long ScanLineStride;
- Description
- Byte offset between the start of two consecutive scanlines.
This value is permitted to be negative, denoting a bitmap
whose content is flipped at the x axis.
|
|
PlaneStride
long PlaneStride;
- Description
- Byte offset between the start of two consecutive planes.
This value is permitted to be negative. If this value is zero,
the bitmap is assumed to be in chunky format, otherwise it is
assumed to be planar. The difference between chunky and
planar layout lies in the way how color channels are
interleaved. For a chunky format, all channel data for a
single pixel lies consecutively in memory. For a planar
layout, the first channel of all pixel is stored consecutive,
followed by the second channel, and so forth.
|
|
ColorSpace
XIntegerBitmapColorSpace ColorSpace;
- Description
- Color space the bitmap colors shall be interpreted within.
Note that the actual pixel layout is specified at the color
space. If this layout describes a palette bitmap format, this
color space describes the index format (plus maybe an extra
alpha channel). The palette itself references another color
space, which describes the layout of the palette entries.
- See also
- XBitmapPalette
|
|
Palette
XBitmapPalette Palette;
- Description
- This member determines whether the bitmap data are actually
indices into a color map.
When set to the nil reference, the bitmap data is assumed to
contain direct color values (to be interpreted according to
the associated color space). If this member references a valid
palette, one of the pixel components as returned by the color
space referenced from the ColorSpace is
required to be of type
ColorComponentTag::INDEX. That component is
then used to index the palette.
|
|
IsMsbFirst
boolean IsMsbFirst;
- Description
- This member determines the bit order (only relevant if a pixel
uses less than 8 bits, of course).
When true, this member denotes that the leftmost pixel from
an 8 bit amount of pixel data consists of the bits starting
with the most significant bit. When false, it's starting
with the least significant bit.
Example: for a 1bpp bitmap, each pixel is represented by
exactly one bit. If this member is true, the first pixel is
the MSB of the first byte, and the eighth pixel is the LSB of
the first byte. If this member is false, it's just the
opposite.
|
|
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


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| Home | Libraries | People | FAQ | More |
When designing the fixed-point negatable
class, particular care has been taken to ensure that it can be easily configured
for efficient use with bare-metal embedded microcontroller systems. These
are microcontroller systems typically designed for control applications.
These kinds of applications often do not have any I/O streaming devices and
they might also lack a dedicated hardware floating-point-unit (FPU). Using
fixed-point can be a sensible choice for mathematical calculations in this
application range.
In order to configure the fixed-point negatable class for efficient use with a bare-metal embedded microcontroller system, (see evaluating derivative example and Real-Time C++, C M Kormanyos Section 9.6), two preprocessor macros need to be defined.
An efficient configuration for a 32-bit microcontroller, for example, is shown below.
#define BOOST_FIXED_POINT_DISABLE_MULTIPRECISION // Do not use Boost.Multiprecision. #define BOOST_FIXED_POINT_DISABLE_IOSTREAM // Do not use I/O streaming. #include <boost/fixed_point/fixed_point.hpp> // Define an efficient 32-bit fixed-point type. typedef boost::fixed_point::negatable<7, -24> fixed_point_type;
| Tip | |
|---|---|
All preprocessor definitions must be defined above the inclusion of any fixed-point header files. |
Here, we have configured for a 32-bit bare-metal microcontroller environment and defined an efficient 32-bit negatable type that has well-optimized C math functions in its precision range.
Consider also a tiny 8-bit microcontroller. The 32-bit fixed-point type shown above might be too bulky for such a tiny microcontroller. In this case, a possible efficient configuration might use the following.
#define BOOST_FIXED_POINT_DISABLE_MULTIPRECISION // Do not use Boost.Multiprecision. #define BOOST_FIXED_POINT_DISABLE_IOSTREAM // Do not use I/O streaming. #include <boost/fixed_point/fixed_point.hpp> // Define an efficient 16-bit fixed-point type. typedef boost::fixed_point::negatable<4, -11> fixed_point_type;
Here, we have configured for a tiny 8-bit bare-metal microcontroller environment by defining an efficient 16-bit negatable type that has well-optimized C math functions within its modest 16-bit precision range.
When using small fixed-point types such as negatable<4,
-11>
or negatable<7,
-24>
, it is important to note that the range
and precision of the fixed-point type can be quite limited in comparison
with, say, built-in floating-point types. The type negatable<7,
-24>
, for example, has approximately 24 decimal
fractional digits of precision to the right of the decimal point and approximately
7 decimal integral digits to the left. The type negatable<4,
-11>
has merely 3-4 decimal fractional digits
of precision to the right of the decimal point and only about 1 decimal integral
digit to the left.
Benchmarks using the fixed-point negatable class have been performed using a variety of mathematical techniques Two main microcontrollers have been used for benchmarking: a 32-bit microcontroller clocked at 24 MHz and a 8-bit microcontroller clocked at 16MHz. Both of these microcontrollers lack a dedicated hardware FPU. Timing results have been obtained with a digital oscilloscope in combination with a standard I/O pin toggle mechanism, as described in Section 9.6 of Real-Time C++, C M Kormanyos.
The following table shows run-time comparisons of negatable<7,
-24>
with built-in single-precision floating-point
for various mathematical calculations. This benchmark has been performed
with a 32-bit microcontroller (without FPU) clocked at 24 MHz. GCC 5.2.0
built with newlib for the target arm-none-eabi
has been used.
Table 5. Comparing speed of fixed-point and floating-point with a 32-bit microcontroller
|
function |
run-time |
run-time 32-bit |
|---|---|---|
|
(1/3) + (9/7) |
0.4 |
2.5 |
|
(1/3) * (9/7) |
1.6 |
2.0 |
|
(1/3) / (9/7) |
6 |
7 |
|
sqrt( 6/10) |
6 |
49 |
|
sin ( 1/ 2) |
6 |
43 |
|
exp ( 7/10) |
12 |
110 |
|
log (13/10) |
10 |
110 |
|
atan( 1/ 2) |
4 |
64 |
|
d/dx[q(x)] |
27 |
70 |
In the final table entry, d/dx represents the first derivative and q(x) represents the quadratic polynomial described in the evaluating derivative example.
All of the calculations have produced approximately 6-7 decimal digits of precision. In general, the fixed-point calculations require less run-time than the floating-point calculations. For certain mathematical functions, the run-time savings can be significant.
If fewer digits of precision are acceptable for the calculation, even further
increases of speed are possible using a less wide fixed-point type such as
negatable<4, -11>
.
The benchmark results in the table below, for instance, represent calculations
of sqrt(6/10)
and sin(1/2)
using both
negatable<4, -11>
and
built-in 32-bit single-precision floating-point.
Table 6. Comparing speed of fixed-point and floating-point with a 32-bit microcontroller
|
Function |
run-time |
run-time 32-bit |
|---|---|---|
|
sqrt( 6/10) |
2.0 |
49 |
|
sin ( 1/ 2) |
2.8 |
43 |
In this comparison, we see a significant run-time advantage for the negatable<4, -11>
fixed-point
type, but at the expense of lower precision. Again, the 32-bit microcontroller
(without FPU) clocked at 24 MHz has been used with GCC 5.2.0 built with newlib
for the target arm-none-eabi
.
When using a small 8-bit microcontroller, a smaller fixed-point type such
as one fitting into a 16-bit integer can result in high performance. The
benchmark results in the table below have been obtained with negatable<4, -11>
running
on an 8-bit microcontroller clocked at 16 MHz. This benchmark has been performed
with GCC 5.3.0 for the target avr-unknown-elf
.
Table 7. Comparing speed of fixed-point and floating-point with an 8-bit microcontroller
|
function |
run-time |
run-time 32-bit |
|---|---|---|
|
(1/3) + (9/7) |
1 |
8 |
|
(1/3) * (9/7) |
9 |
10 |
|
(1/3) / (9/7) |
44 |
31 |
|
sqrt( 6/10) |
18 |
31 |
|
sin ( 1/ 2) |
36 |
100 |
|
exp ( 7/10) |
81 |
180 |
|
log (13/10) |
53 |
140 |
|
atan( 1/ 2) |
41 |
150 |
|
d/dx[q(x)] |
170 |
290 |
Another perspective on resource consumption can be obtained by measuring the size of the code used in a benchmark.
Consider the sqrt(6/10)
calculation performed on the 32-bit microcontroller
comparing negatable<7, -24>
with
built-in 32-bit single-precision floating-point. The following code sizes
were obtained for this particular benchmark.
Table 8. Comparing code size with a 32-bit Microcontroller
|
Function |
|
32-bit |
|---|---|---|
|
|
1,900 - 1,200 = 700 |
4,400 - 1,200 = 3,200 |
Here the final code consumption is shown as the result of subtraction. The subtracted amount arises from the code required to implement a minimalistic cooperative-multitasking scheduler and skinny hardware abstraction layer, as described in Chaps. 8, 9 and 11 in Real-Time C++, C M Kormanyos. In this benchmark, the code contributions from the (pre-main) startup and the interrupt vector table have been ignored.
The code can be squeezed even further if a less wide fixed-point type is
used. The result below shows the code size for the sqrt(6/10)
calculation
performed with negatable<4,
-11>
on the 32-bit microcontroller. The comparison
is with with built-in 32-bit single-precision floating-point.
Table 9. Comparing code size with a 32-bit Microcontroller
|
Function |
|
32-bit |
|---|---|---|
|
|
1,700 - 1,300 = 400 |
4,400 - 1,200 = 3,200 |
It can be observed that the fixed-point calculations in these size benchmarks require significantly less code than the corresponding floating-point calculations. For a large fixed-point project, however, the resulting code size can vary significantly depending on the compiler's inlining characteristics and optimization abilities. This is because the fixed-point library is template code. It is, therefore, a good idea to periodically check the code size of a fixed-point project and adjust the compiler parameters according to the needs of the project.
In all of the benchmarks (for both speed measurements as well as size measurements),
GCC has been used with optimization setting -O2 (see https://gcc.gnu.org/onlinedocs/gcc-6.1.0/gcc/Optimize-Options.html#Optimize-Options).
Inline functions have been enabled with inline function-depth set to 32 lines
using the two compiler options -finline-functions
and -finline-limit=32
.


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I am an extremely creative and productive with team player or individual player, high self-motivation, and high ability to self-learning.
I have lot experiences using DotNet as my main development tool. But currently I love JS, last year I have developed JS framework to do automation data binder base on AJAX responds (Like AngularJS framework).
You can reach all of my public library (open source project), from Github. And see my other profile (StackOverflow, LinkedIn, WordPress, Facebook) via Social Media buttons on the right side, or on top of this page.
2003 - 2009
3,13 of 4,00 GPA
2000 - 2003
Taking IPA (Ilmu Pengetahuan Alam) major.
1997 - 2000
Equivalen with High School level (SMP).
1991 - 1997
-
Be Technopreneur Java Mobile
Pembuatan Media Pembelajaran Secara Visual
Gelombang 3G Dunia Mobile
Perspektif Perkembangan ICT
Speedy Goes To School
Windows Server System Indonesia
Windows Based Hosting
Kamoro Maxima Integra is an outsourcing company and assigning me for AIA Financial. At AIA Financial I've handled some project as listed below (included but not limited):
Accelist Lentera Indonesia is an outsourcing company, which assigning me for several companies:
This part only showing my freelancing experiences. I have done some projects as listed below:
MyIndo Cyber Media is an outsourcing company, which assigning me for Chevron The projects I have done is:
Currently I love JavaScript so much. Two years ago I have developed JavaScript Framework with a lot of ability, such as Data Binder (just like angularJS), AJAX and common JavaScript datatype extension (string, number, array, datettime), compare tools, etc.
You can see (anything you want, fork, download, or direct using, lol) my JavaScript library from octapushJS.
Oh, you can see the list below for my JavaScript framework ability:
I have created a library for .Net too, you can see my dotnet library from octapush.utilities
Starting from 2007 I have used .Net technology, I think is a long time enough just to knowing:
I love versioning (it's so incredible tool, I think). So Microsoft versioning application which called Team Foundation Server (TFS) and Visual Studio Online (VSO) is the very important part for my Microsoft projects.
But, I will not tell you about how my ability on repository/versioning only. Another capability on handling TFS is:
Note:
*) We can be separating each development stage into three (or more) kind (development stage, SIT stage, UAT stage) in the same repository.
**) While customizing TFS/VSO, usually I am using Batch Script, PowerShell, and/or .Net (VB / C#).
To be a good programmer, I add some database skills too. Start from creating database structures Tables, Views, Store Procedures, Functions, to Queries, etc...
For queryable database engine I have used is:
And for No-SQL database engine I have used is:
Actually, Web designing is not my passion. But still, I have the skill to do web designing by using HTML5 and CSS3.
Again, my passion is on programming area.
But, based on my freelance experiences, I have to manage, tracking, and reporting my project progress. For fast progress and result (also customizable) of my project, usually, I have used an Agile development method.
The tools that supporting Agile development that I have used are:
It's too many technologies I have learned, I feel tired to filling out and describing for each my skills in here. So, this is my complete skill list: C#.Net VB.Net VB 6 (classic) VBScript VBA SQL Server Integration Services (SSIS) SQL Server Reporting Services (SSRS) JavaScript PHP 4 PHP 5 Java Powershell Team Foundation Server (TFS) Web Service (Rest and/or Restful) Ms.SQL MySQL Sybase SQL Anywhere Ms.Access Firebase jQuery LiteDB AngularJS ArcGIS MapInfo HTML5 CSS3 Bootstrap Github Github PR Visual Studio Online (VSO) Github Bitbucket Trello etc..
Need a prove? let's check who has been endorsing me on my LinkedIn Profile for each my skills.
Mr. Fadhly is hard worker. Has long stress tollerance. He always did his job fastly. He is my OO Javascript master.
Nice to work with him.
Hello Fadhly,
Fadhly is a very kind people who has a very strong technical knowledge especially in the .net programming, he is open minded, solid to work as a team, and he also a hardworker. I very recommended this people if you want to make some cool program either in the web based platform or desktop platform.
Good to be part of the team.
Fadhly adalah senior programmer .Net, (WebForm , MVC, dan WEB API) selain itu pernah membuat aplikasi Game dengan PHP dan Js, saat ini dia sedang mengembangkan FrameWork JS seperti angular yang di namakan Octapush.Js, dan FrameWork .Net (Octapush.Utilities), dan cerdas dalam Solved Database Beliau sangat layak dikatakan sbg seorang Analyst dan Senior Programmer.
Fadhly adalah senior programmer yg banyak memiliki pengalaman khususnya untuk .Net programming, pengusaan java script dan jQuery nya sangat tinggi. Beliau banyak mengerjakan project2 di Perusahaan besar baik dengan Tim atau Individu. Beliau sangat layak dikatakan sbg Senior Programmer.
Smart programmer!
Fadly seorang yang memiliki skill I.T yang banyak, khususnya di .NET dan JavaScript, JQuery. Fadhly juga tidak segan untuk sharing knowledge/membantu rekan satu team jika ada permasalahan, problem solver, kompeten dan bisa di andalkan.
Senang pernah 1 team dengan Fadhly. Saya banyak belajar dan dapat ilmu banyak dari beliau.


2048
A very simple implementation.
Rules
Use the arrow keys to move pieces.
Pieces of same value will combine.