- Priority Queueing Simulation - 1 Update
- About Java and Delphi and Freepascal.. - 3 Updates
- Yet more precision about the invariants of a system.. - 1 Update
| aminer68@gmail.com: Jan 27 10:56AM -0800 Hello, Priority Queueing Simulation A round-robin queuing scheduler allows tasks to have equal access to the processor. The addition of priority levels allows more important tasks to be completed first. However this scenario could result in lower level tasks never gaining access to the processor. This situation is known as starvation. Here is two Strategies to Prevent Starvation: Read more here: https://www.nku.edu/~mcguffeej1/Franzen_poster.pdf Thank you, Amine Moulay Ramdane. |
| Wisdom90 <d@d.d>: Jan 27 12:15PM -0500 Hello, About Java and Delphi and Freepascal.. I have just read the following webpage: Java is not a safe language https://lemire.me/blog/2019/03/28/java-is-not-a-safe-language/ But as you have noticed the webpage says: - Java does not trap overflows But Delphi and Freepascal do trap overflows. And the webpage says: - Java lacks null safety But Delphi has null safety since i have just posted about it by saying the following: Here is MyNullable library for Delphi and FreePascal that brings null safety.. Java lacks null safety. When a function receives an object, this object might be null. That is, if you see 'String s' in your code, you often have no way of knowing whether 's' contains an actually String unless you check at runtime. Can you guess whether programmers always check? They do not, of course, In practice, mission-critical software does crash without warning due to null values. We have two decades of examples. In Swift or Kotlin, you have safe calls or optionals as part of the language. Here is MyNullable library for Delphi and FreePascal that brings null safety, you can read the html file inside the zip to know how it works, and you can download it from my website here: https://sites.google.com/site/scalable68/null-safety-library-for-delphi-and-freepascal And the webpage says: - Java allows data races But for Delphi and Freepascal i have just written about how to prevent data races by saying the following: Yet more precision about the invariants of a system.. I was just thinking about Petri nets , and i have studied more Petri nets, they are useful for parallel programming, and what i have noticed by studying them, is that there is two methods to prove that there is no deadlock in the system, there is the structural analysis with place invariants that you have to mathematically find, or you can use the reachability tree, but we have to notice that the structural analysis of Petri nets learns you more, because it permits you to prove that there is no deadlock in the system, and the place invariants are mathematically calculated by the following system of the given Petri net: Transpose(vector) * Incidence matrix = 0 So you apply the Gaussian Elimination or the Farkas algorithm to the incidence matrix to find the Place invariants, and as you will notice those place invariants calculations of the Petri nets look like Markov chains in mathematics, with there vector of probabilities and there transition matrix of probabilities, and you can, using Markov chains mathematically calculate where the vector of probabilities will "stabilize", and it gives you a very important information, and you can do it by solving the following mathematical system: Unknown vector1 of probabilities * transition matrix of probabilities = Unknown vector1 of probabilities. Solving this system of equations is very important in economics and other fields, and you can notice that it is like calculating the invariants , because the invariant in the system above is the vector1 of probabilities that is obtained, and this invariant, like in the invariants of the structural analysis of Petri nets, gives you a very important information about the system, like where market shares will stabilize that is calculated this way in economics. About reachability analysis of a Petri net.. As you have noticed in my Petri nets tutorial example (read below), i am analysing the liveness of the Petri net, because there is a rule that says: If a Petri net is live, that means that it is deadlock-free. Because reachability analysis of a Petri net with Tina gives you the necessary information about boundedness and liveness of the Petri net. So if it gives you that the Petri net is "live" , so there is no deadlock in it. Tina and Partial order reduction techniques.. With the advancement of computer technology, highly concurrent systems are being developed. The verification of such systems is a challenging task, as their state space grows exponentially with the number of processes. Partial order reduction is an effective technique to address this problem. It relies on the observation that the effect of executing transitions concurrently is often independent of their ordering. Tina is using "partial-order" reduction techniques aimed at preventing combinatorial explosion, Read more here to notice it: http://projects.laas.fr/tina/papers/qest06.pdf About modelizations and detection of race conditions and deadlocks in parallel programming.. I have just taken further a look at the following project in Delphi called DelphiConcurrent by an engineer called Moualek Adlene from France: https://github.com/moualek-adlene/DelphiConcurrent/blob/master/DelphiConcurrent.pas And i have just taken a look at the following webpage of Dr Dobb's journal: Detecting Deadlocks in C++ Using a Locks Monitor https://www.drdobbs.com/detecting-deadlocks-in-c-using-a-locks-m/184416644 And i think that both of them are using technics that are not as good as analysing deadlocks with Petri Nets in parallel applications , for example the above two methods are only addressing locks or mutexes or reader-writer locks , but they are not addressing semaphores or event objects and such other synchronization objects, so they are not good, this is why i have written a tutorial that shows my methodology of analysing and detecting deadlocks in parallel applications with Petri Nets, my methodology is more sophisticated because it is a generalization and it modelizes with Petri Nets the broader range of synchronization objects, and in my tutorial i will add soon other synchronization objects, you have to look at it, here it is: https://sites.google.com/site/scalable68/how-to-analyse-parallel-applications-with-petri-nets You have to get the powerful Tina software to run my Petri Net examples inside my tutorial, here is the powerful Tina software: http://projects.laas.fr/tina/ Also to detect race conditions in parallel programming you have to take a look at the following new tutorial that uses the powerful Spin tool: https://mirrors.edge.kernel.org/pub/linux/kernel/people/paulmck/perfbook/perfbook.html This is how you will get much more professional at detecting deadlocks and race conditions in parallel programming. And about memory safety of Delphi and Freepascal, here is what i said: I have just read the following webpage about memory safety: Microsoft: 70 percent of all security bugs are memory safety issues https://www.zdnet.com/article/microsoft-70-percent-of-all-security-bugs-are-memory-safety-issues/ And it says: "Users who often read vulnerability reports come across terms over and over again. Terms like buffer overflow, race condition, page fault, null pointer, stack exhaustion, heap exhaustion/corruption, use after free, or double free --all describe memory safety vulnerabilities." So as you will notice below, that the following memory safety problems has been solved in Delphi: And I have just read the following webpage about "Fearless Security: Memory safety": https://hacks.mozilla.org/2019/01/fearless-security-memory-safety/ Here is the memory safety problems: 1- Misusing Free (use-after-free, double free) I have solved this in Delphi and Freepascal by inventing a "Scalable" reference counting with efficient support for weak references. Read below about it. 2- Uninitialized variables This can be detected by the compilers of Delphi and Freepascal. 3- Dereferencing Null pointers I have solved this in Delphi and Freepascal by inventing a "Scalable" reference counting with efficient support for weak references. Read below about it. 4- Buffer overflow and underflow This has been solved in Delphi by using madExcept, read here about it: http://help.madshi.net/DebugMm.htm You can buy it from here: http://www.madshi.net/ There remains also the stack exhaustion memory safety problem, and here is how to detect it in Delphi: Call the function "DoStackOverflow" below once from your code and you'll get the EStackOverflow error raised by Delphi with the message "stack overflow", and you can print the line of the source code where EStackOverflow is raised with JCLDebug and such: ---- function DoStackOverflow : integer; begin result := 1 + DoStackOverflow; end; --- About my scalable algorithms inventions.. I am a white arab, and i am a gentleman type of person, and i think that you know me too by my poetry that i wrote in front of you and that i posted here, but i am also a more serious computer developer, and i am also an inventor who has invented many scalable algorithms, read about them on my writing below: Here is my last scalable algorithm invention, read what i have just responded in comp.programming.threads: About my LRU scalable algorithm.. On 10/16/2019 7:48 AM, Bonita Montero on comp.programming.threads wrote: > in locked mode in very rare cases. And as I said inserting and > flushing is conventional locked access. > So the quest is for you: Can you guess what I did? And here is what i have just responded: I think i am also smart, so i have just quickly found a solution that is scalable and that is not your solution, so it needs my hashtable that is scalable and it needs my fully scalable FIFO queue that i have invented. And i think i will not patent it. But my solution is not Lockfree, it uses locks like in a Lock striping manner and it is scalable. And read about my other scalable algorithms inventions on my writing below: About the buffer overflow problem.. I wrote yesterday about buffer overflow in Delphi and Freepascal.. I think there is a "higher" abstraction in Delphi and Freepascal that does the job very well of avoiding buffer overflow, and it is the TMemoryStream class, since it behaves also like a pointer and it supports reallocmem() and freemem() on the pointer but with a higher level abstraction, look for example at my following example in Delphi and Freepascal, you will notice that contrary to pointers , that the memory stream is adapting with writebuffer() without the need of reserving the memory, and this is why it avoids the buffer overflow problem, read the following example to notice how i am using it with a PAnsichar type: ======================================== Program test; uses system.classes,system.sysutils; var P: PAnsiChar; Begin P:='Amine'; mem:=TMemorystream.create; mem.position:=0; mem.writebuffer(pointer(p)^,6); mem.position:=0; writeln(PAnsichar(mem.memory)); end. =================================== So since Delphi and Freepascal also detect the buffer overflow on dynamic arrays , so i think that Delphi and Freepascal are powerful tools. Read my previous thoughts below to understand more: And I have just read the following webpage about "Fearless Security: Memory safety": https://hacks.mozilla.org/2019/01/fearless-security-memory-safety/ Here is the memory safety problems: 1- Misusing Free (use-after-free, double free) I have solved this in Delphi and Freepascal by inventing a "Scalable" reference counting with efficient support for weak references. Read below about it. 2- Uninitialized variables This can be detected by the compilers of Delphi and Freepascal. 3- Dereferencing Null pointers I have solved this in Delphi and Freepascal by inventing a "Scalable" reference counting with efficient support for weak references. Read below about it. 4- Buffer overflow and underflow This has been solved in Delphi by using madExcept, read here about it: http://help.madshi.net/DebugMm.htm You can buy it from here: http://www.madshi.net/ And about race conditions and deadlocks problems and more, read my following thoughts to understand: I will reformulate more smartly what about race conditions detection in Rust, so read it carefully: You can think of the borrow checker of Rust as a validator for a locking system: immutable references are shared read locks and mutable references are exclusive write locks. Under this mental model, accessing data via two independent write locks is not a safe thing to do, and modifying data via a write lock while there are readers alive is not safe either. So as you are noticing that the "mutable" references in Rust follow the Read-Write Lock pattern, so this is not good, because it is not like more fine-grained parallelism that permits us to run the writes in "parallel" and gain more performance from parallelizing the writes. Read more about Rust and Delphi and my inventions.. I think the spirit of Rust is like the spirit of ADA, they are especially designed for the very high standards of safety, like those of ADA, "but" i don't think we have to fear race conditions that Rust solve, because i think that race conditions are not so difficult to avoid when you are a decent knowledgeable programmer in parallel programming, so you have to understand what i mean, now we have to talk about the rest of the safety guaranties of Rust, there remain the problem of Deadlocks, and i think that Rust is not solving this problem, but i have provided you with an enhanced DelphiConcurrent library for Delphi and Freepascal that detects deadlocks, and there is also the Memory Safety guaranties of Rust, here they are: 1- No Null Pointer Dereferences 2- No Dangling Pointers 3- No Buffer Overruns But notice that I have solved the number 1 and number 2 by inventing my scalable reference counting with efficient support for weak references for Delphi and Freepascal, read below to notice it, and for number 3 read my following thoughts to understand: More about research and software development.. I have just looked at the following new video: Why is coding so hard... https://www.youtube.com/watch?v=TAAXwrgd1U8 I am understanding this video, but i have to explain my work: I am not like this techlead in the video above, because i am also an "inventor" that has invented many scalable algorithms and there implementions, i am also inventing effective abstractions, i give you an example: Read the following of the senior research scientist that is called Dave Dice: Preemption tolerant MCS locks https://blogs.oracle.com/dave/preemption-tolerant-mcs-locks As you are noticing he is trying to invent a new lock that is preemption tolerant, but his lock lacks some important characteristics, this is why i have just invented a new Fast Mutex that is adaptative and that is much much better and i think mine is the "best", and i think you will not find it anywhere, my new Fast Mutex has the following characteristics: 1- Starvation-free 2- Good fairness 3- It keeps efficiently and very low the cache coherence traffic 4- Very good fast path performance (it has the same performance as the scalable MCS lock when there is contention.) 5- And it has a decent preemption tolerance. this is how i am an "inventor", and i have also invented other scalable algorithms such as a scalable reference counting with efficient support for weak references, and i have invented a fully scalable Threadpool, and i have also invented a Fully scalable FIFO queue, and i have also invented other scalable algorithms and there inmplementations, and i think i will sell some of them to Microsoft or to Google or Embarcadero or such software companies. Read my following writing to know me more: More about computing and parallel computing.. The important guaranties of Memory Safety in Rust are: |
| aminer68@gmail.com: Jan 27 09:16AM -0800 Hello, About Java and Delphi and Freepascal.. I have just read the following webpage: Java is not a safe language https://lemire.me/blog/2019/03/28/java-is-not-a-safe-language/ But as you have noticed the webpage says: - Java does not trap overflows But Delphi and Freepascal do trap overflows. And the webpage says: - Java lacks null safety But Delphi has null safety since i have just posted about it by saying the following: Here is MyNullable library for Delphi and FreePascal that brings null safety.. Java lacks null safety. When a function receives an object, this object might be null. That is, if you see 'String s' in your code, you often have no way of knowing whether 's' contains an actually String unless you check at runtime. Can you guess whether programmers always check? They do not, of course, In practice, mission-critical software does crash without warning due to null values. We have two decades of examples. In Swift or Kotlin, you have safe calls or optionals as part of the language. Here is MyNullable library for Delphi and FreePascal that brings null safety, you can read the html file inside the zip to know how it works, and you can download it from my website here: https://sites.google.com/site/scalable68/null-safety-library-for-delphi-and-freepascal And the webpage says: - Java allows data races But for Delphi and Freepascal i have just written about how to prevent data races by saying the following: Yet more precision about the invariants of a system.. I was just thinking about Petri nets , and i have studied more Petri nets, they are useful for parallel programming, and what i have noticed by studying them, is that there is two methods to prove that there is no deadlock in the system, there is the structural analysis with place invariants that you have to mathematically find, or you can use the reachability tree, but we have to notice that the structural analysis of Petri nets learns you more, because it permits you to prove that there is no deadlock in the system, and the place invariants are mathematically calculated by the following system of the given Petri net: Transpose(vector) * Incidence matrix = 0 So you apply the Gaussian Elimination or the Farkas algorithm to the incidence matrix to find the Place invariants, and as you will notice those place invariants calculations of the Petri nets look like Markov chains in mathematics, with there vector of probabilities and there transition matrix of probabilities, and you can, using Markov chains mathematically calculate where the vector of probabilities will "stabilize", and it gives you a very important information, and you can do it by solving the following mathematical system: Unknown vector1 of probabilities * transition matrix of probabilities = Unknown vector1 of probabilities. Solving this system of equations is very important in economics and other fields, and you can notice that it is like calculating the invariants , because the invariant in the system above is the vector1 of probabilities that is obtained, and this invariant, like in the invariants of the structural analysis of Petri nets, gives you a very important information about the system, like where market shares will stabilize that is calculated this way in economics. About reachability analysis of a Petri net.. As you have noticed in my Petri nets tutorial example (read below), i am analysing the liveness of the Petri net, because there is a rule that says: If a Petri net is live, that means that it is deadlock-free. Because reachability analysis of a Petri net with Tina gives you the necessary information about boundedness and liveness of the Petri net. So if it gives you that the Petri net is "live" , so there is no deadlock in it. Tina and Partial order reduction techniques.. With the advancement of computer technology, highly concurrent systems are being developed. The verification of such systems is a challenging task, as their state space grows exponentially with the number of processes. Partial order reduction is an effective technique to address this problem. It relies on the observation that the effect of executing transitions concurrently is often independent of their ordering. Tina is using "partial-order" reduction techniques aimed at preventing combinatorial explosion, Read more here to notice it: http://projects.laas.fr/tina/papers/qest06.pdf About modelizations and detection of race conditions and deadlocks in parallel programming.. I have just taken further a look at the following project in Delphi called DelphiConcurrent by an engineer called Moualek Adlene from France: https://github.com/moualek-adlene/DelphiConcurrent/blob/master/DelphiConcurrent.pas And i have just taken a look at the following webpage of Dr Dobb's journal: Detecting Deadlocks in C++ Using a Locks Monitor https://www.drdobbs.com/detecting-deadlocks-in-c-using-a-locks-m/184416644 And i think that both of them are using technics that are not as good as analysing deadlocks with Petri Nets in parallel applications , for example the above two methods are only addressing locks or mutexes or reader-writer locks , but they are not addressing semaphores or event objects and such other synchronization objects, so they are not good, this is why i have written a tutorial that shows my methodology of analysing and detecting deadlocks in parallel applications with Petri Nets, my methodology is more sophisticated because it is a generalization and it modelizes with Petri Nets the broader range of synchronization objects, and in my tutorial i will add soon other synchronization objects, you have to look at it, here it is: https://sites.google.com/site/scalable68/how-to-analyse-parallel-applications-with-petri-nets You have to get the powerful Tina software to run my Petri Net examples inside my tutorial, here is the powerful Tina software: http://projects.laas.fr/tina/ Also to detect race conditions in parallel programming you have to take a look at the following new tutorial that uses the powerful Spin tool: https://mirrors.edge.kernel.org/pub/linux/kernel/people/paulmck/perfbook/perfbook.html This is how you will get much more professional at detecting deadlocks and race conditions in parallel programming. And about memory safety of Delphi and Freepascal, here is what i said: I have just read the following webpage about memory safety: Microsoft: 70 percent of all security bugs are memory safety issues https://www.zdnet.com/article/microsoft-70-percent-of-all-security-bugs-are-memory-safety-issues/ And it says: "Users who often read vulnerability reports come across terms over and over again. Terms like buffer overflow, race condition, page fault, null pointer, stack exhaustion, heap exhaustion/corruption, use after free, or double free --all describe memory safety vulnerabilities." So as you will notice below, that the following memory safety problems has been solved in Delphi: And I have just read the following webpage about "Fearless Security: Memory safety": https://hacks.mozilla.org/2019/01/fearless-security-memory-safety/ Here is the memory safety problems: 1- Misusing Free (use-after-free, double free) I have solved this in Delphi and Freepascal by inventing a "Scalable" reference counting with efficient support for weak references. Read below about it. 2- Uninitialized variables This can be detected by the compilers of Delphi and Freepascal. 3- Dereferencing Null pointers I have solved this in Delphi and Freepascal by inventing a "Scalable" reference counting with efficient support for weak references. Read below about it. 4- Buffer overflow and underflow This has been solved in Delphi by using madExcept, read here about it: http://help.madshi.net/DebugMm.htm You can buy it from here: http://www.madshi.net/ There remains also the stack exhaustion memory safety problem, and here is how to detect it in Delphi: Call the function "DoStackOverflow" below once from your code and you'll get the EStackOverflow error raised by Delphi with the message "stack overflow", and you can print the line of the source code where EStackOverflow is raised with JCLDebug and such: ---- function DoStackOverflow : integer; begin result := 1 + DoStackOverflow; end; --- About my scalable algorithms inventions.. I am a white arab, and i am a gentleman type of person, and i think that you know me too by my poetry that i wrote in front of you and that i posted here, but i am also a more serious computer developer, and i am also an inventor who has invented many scalable algorithms, read about them on my writing below: Here is my last scalable algorithm invention, read what i have just responded in comp.programming.threads: About my LRU scalable algorithm.. On 10/16/2019 7:48 AM, Bonita Montero on comp.programming.threads wrote: > in locked mode in very rare cases. And as I said inserting and > flushing is conventional locked access. > So the quest is for you: Can you guess what I did? And here is what i have just responded: I think i am also smart, so i have just quickly found a solution that is scalable and that is not your solution, so it needs my hashtable that is scalable and it needs my fully scalable FIFO queue that i have invented. And i think i will not patent it. But my solution is not Lockfree, it uses locks like in a Lock striping manner and it is scalable. And read about my other scalable algorithms inventions on my writing below: About the buffer overflow problem.. I wrote yesterday about buffer overflow in Delphi and Freepascal.. I think there is a "higher" abstraction in Delphi and Freepascal that does the job very well of avoiding buffer overflow, and it is the TMemoryStream class, since it behaves also like a pointer and it supports reallocmem() and freemem() on the pointer but with a higher level abstraction, look for example at my following example in Delphi and Freepascal, you will notice that contrary to pointers , that the memory stream is adapting with writebuffer() without the need of reserving the memory, and this is why it avoids the buffer overflow problem, read the following example to notice how i am using it with a PAnsichar type: ======================================== Program test; uses system.classes,system.sysutils; var P: PAnsiChar; Begin P:='Amine'; mem:=TMemorystream.create; mem.position:=0; mem.writebuffer(pointer(p)^,6); mem.position:=0; writeln(PAnsichar(mem.memory)); end. =================================== So since Delphi and Freepascal also detect the buffer overflow on dynamic arrays , so i think that Delphi and Freepascal are powerful tools. Read my previous thoughts below to understand more: And I have just read the following webpage about "Fearless Security: Memory safety": https://hacks.mozilla.org/2019/01/fearless-security-memory-safety/ Here is the memory safety problems: 1- Misusing Free (use-after-free, double free) I have solved this in Delphi and Freepascal by inventing a "Scalable" reference counting with efficient support for weak references. Read below about it. 2- Uninitialized variables This can be detected by the compilers of Delphi and Freepascal. 3- Dereferencing Null pointers I have solved this in Delphi and Freepascal by inventing a "Scalable" reference counting with efficient support for weak references. Read below about it. 4- Buffer overflow and underflow This has been solved in Delphi by using madExcept, read here about it: http://help.madshi.net/DebugMm.htm You can buy it from here: http://www.madshi.net/ And about race conditions and deadlocks problems and more, read my following thoughts to understand: I will reformulate more smartly what about race conditions detection in Rust, so read it carefully: You can think of the borrow checker of Rust as a validator for a locking system: immutable references are shared read locks and mutable references are exclusive write locks. Under this mental model, accessing data via two independent write locks is not a safe thing to do, and modifying data via a write lock while there are readers alive is not safe either. So as you are noticing that the "mutable" references in Rust follow the Read-Write Lock pattern, so this is not good, because it is not like more fine-grained parallelism that permits us to run the writes in "parallel" and gain more performance from parallelizing the writes. Read more about Rust and Delphi and my inventions.. I think the spirit of Rust is like the spirit of ADA, they are especially designed for the very high standards of safety, like those of ADA, "but" i don't think we have to fear race conditions that Rust solve, because i think that race conditions are not so difficult to avoid when you are a decent knowledgeable programmer in parallel programming, so you have to understand what i mean, now we have to talk about the rest of the safety guaranties of Rust, there remain the problem of Deadlocks, and i think that Rust is not solving this problem, but i have provided you with an enhanced DelphiConcurrent library for Delphi and Freepascal that detects deadlocks, and there is also the Memory Safety guaranties of Rust, here they are: 1- No Null Pointer Dereferences 2- No Dangling Pointers 3- No Buffer Overruns But notice that I have solved the number 1 and number 2 by inventing my scalable reference counting with efficient support for weak references for Delphi and Freepascal, read below to notice it, and for number 3 read my following thoughts to understand: More about research and software development.. I have just looked at the following new video: Why is coding so hard... https://www.youtube.com/watch?v=TAAXwrgd1U8 I am understanding this video, but i have to explain my work: I am not like this techlead in the video above, because i am also an "inventor" that has invented many scalable algorithms and there implementions, i am also inventing effective abstractions, i give you an example: Read the following of the senior research scientist that is called Dave Dice: Preemption tolerant MCS locks https://blogs.oracle.com/dave/preemption-tolerant-mcs-locks As you are noticing he is trying to invent a new lock that is preemption tolerant, but his lock lacks some important characteristics, this is why i have just invented a new Fast Mutex that is adaptative and that is much much better and i think mine is the "best", and i think you will not find it anywhere, my new Fast Mutex has the following characteristics: 1- Starvation-free 2- Good fairness 3- It keeps efficiently and very low the cache coherence traffic 4- Very good fast path performance (it has the same performance as the scalable MCS lock when there is contention.) 5- And it has a decent preemption tolerance. this is how i am an "inventor", and i have also invented other scalable algorithms such as a scalable reference counting with efficient support for weak references, and i have invented a fully scalable Threadpool, and i have also invented a Fully scalable FIFO queue, and i have also invented other scalable algorithms and there inmplementations, and i think i will sell some of them to Microsoft or to Google or Embarcadero or such software companies. Read my following writing to know me more: More about computing and parallel computing.. The important guaranties of Memory Safety in Rust are: 1- No Null Pointer Dereferences 2- No Dangling Pointers 3- No Buffer Overruns I think i have solved Null Pointer Dereferences and also solved |
| Bonita Montero <Bonita.Montero@gmail.com>: Jan 27 06:49PM +0100 > About my LRU scalable algorithm.. Your LRU-algorithm ? Where is it ? >> So the quest is for you: Can you guess what I did? > And here is what i have just responded: > I think i am also smart, ... Then show me your LRU-code. |
| aminer68@gmail.com: Jan 27 05:49AM -0800 Hello, Yet more precision about the invariants of a system.. I was just thinking about Petri nets , and i have studied more Petri nets, they are useful for parallel programming, and what i have noticed by studying them, is that there is two methods to prove that there is no deadlock in the system, there is the structural analysis with place invariants that you have to mathematically find, or you can use the reachability tree, but we have to notice that the structural analysis of Petri nets learns you more, because it permits you to prove that there is no deadlock in the system, and the place invariants are mathematically calculated by the following system of the given Petri net: Transpose(vector) * Incidence matrix = 0 So you apply the Gaussian Elimination or the Farkas algorithm to the incidence matrix to find the Place invariants, and as you will notice those place invariants calculations of the Petri nets look like Markov chains in mathematics, with there vector of probabilities and there transition matrix of probabilities, and you can, using Markov chains mathematically calculate where the vector of probabilities will "stabilize", and it gives you a very important information, and you can do it by solving the following mathematical system: Unknown vector1 of probabilities * transition matrix of probabilities = Unknown vector1 of probabilities. Solving this system of equations is very important in economics and other fields, and you can notice that it is like calculating the invariants , because the invariant in the system above is the vector1 of probabilities that is obtained, and this invariant, like in the invariants of the structural analysis of Petri nets, gives you a very important information about the system, like where market shares will stabilize that is calculated this way in economics. About reachability analysis of a Petri net.. As you have noticed in my Petri nets tutorial example (read below), i am analysing the liveness of the Petri net, because there is a rule that says: If a Petri net is live, that means that it is deadlock-free. Because reachability analysis of a Petri net with Tina gives you the necessary information about boundedness and liveness of the Petri net. So if it gives you that the Petri net is "live" , so there is no deadlock in it. Tina and Partial order reduction techniques.. With the advancement of computer technology, highly concurrent systems are being developed. The verification of such systems is a challenging task, as their state space grows exponentially with the number of processes. Partial order reduction is an effective technique to address this problem. It relies on the observation that the effect of executing transitions concurrently is often independent of their ordering. Tina is using "partial-order" reduction techniques aimed at preventing combinatorial explosion, Read more here to notice it: http://projects.laas.fr/tina/papers/qest06.pdf About modelizations and detection of race conditions and deadlocks in parallel programming.. I have just taken further a look at the following project in Delphi called DelphiConcurrent by an engineer called Moualek Adlene from France: https://github.com/moualek-adlene/DelphiConcurrent/blob/master/DelphiConcurrent.pas And i have just taken a look at the following webpage of Dr Dobb's journal: Detecting Deadlocks in C++ Using a Locks Monitor https://www.drdobbs.com/detecting-deadlocks-in-c-using-a-locks-m/184416644 And i think that both of them are using technics that are not as good as analysing deadlocks with Petri Nets in parallel applications , for example the above two methods are only addressing locks or mutexes or reader-writer locks , but they are not addressing semaphores or event objects and such other synchronization objects, so they are not good, this is why i have written a tutorial that shows my methodology of analysing and detecting deadlocks in parallel applications with Petri Nets, my methodology is more sophisticated because it is a generalization and it modelizes with Petri Nets the broader range of synchronization objects, and in my tutorial i will add soon other synchronization objects, you have to look at it, here it is: https://sites.google.com/site/scalable68/how-to-analyse-parallel-applications-with-petri-nets You have to get the powerful Tina software to run my Petri Net examples inside my tutorial, here is the powerful Tina software: http://projects.laas.fr/tina/ Also to detect race conditions in parallel programming you have to take a look at the following new tutorial that uses the powerful Spin tool: https://mirrors.edge.kernel.org/pub/linux/kernel/people/paulmck/perfbook/perfbook.html This is how you will get much more professional at detecting deadlocks and race conditions in parallel programming. Thank you, Amine Moulay Ramdane. |
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