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This chapter discusses design and coding issues aimed at exploiting parallelism. This chapter will also provide some help with the terminology and concepts of multithreaded programming and synchronization. We refer to thread synchronization concepts in several other places in the book.
If your exposure to those concepts is limited, Chapter 15 should help level the playing field. Chapter 16 takes a look at the underlying system. Top-notch performance also necessitates a rudimentary understanding of underlying operating systems and processor architectures. Issues such as caching, paging, and threading are discussed here.
The Tracing War Story Every software product we have ever worked on contained tracing functionality in one form or another.
Any time your source code exceeds a few thousand lines, tracing becomes essential. It is important for debugging, maintaining, and understanding execution flow of nontrivial software. You would not expect a trace discussion in a performance book but the reality is, on more than one occasion, we have run into severe performance degradation due to poor implementations of tracing. Even slight inefficiencies can have a dramatic effect on performance.
It is simple and familiar.
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We don't have to drown you in a sea of irrelevant details in order to highlight the important issues. Programmers can define a Trace object in each function that they want to trace, and the Trace class can write a message on function entry and function exit. The Trace objects will add extra execution overhead, but they will help a programmer find problems without using a debugger.
This is definitely something your customers will not be able to do unless you jump on the free software bandwagon and ship them your source code. Alternatively, you can control tracing dynamically by communicating with the running program.
It is assumed that tracing will be turned on only during problem determination. During normal operation, tracing would be inactive by default, and we expect our code to exhibit peak performance.
For that to happen, the trace overhead must be minimal. A typical trace statement will look something along the lines of t. Even when tracing is off, we still must create the string argument that is passed in to the debug function. The overhead of creating and destroying those string and Trace objects is at best hundreds of instructions.
In typical OO code where functions are short and call frequencies are high, trace overhead could easily degrade performance by an order of magnitude. This is not a farfetched figment of our imagination. We have actually experienced it in a reallife product implementation. It is an educational experience to delve into this particular horror story in more detail.
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Our first attempt backfired due to atrocious performance. Our Initial Trace Implementation Our intent was to have the trace object log event messages such as entering a function, leaving a function, and possibly other information of interest between those two events.
Trace objects popped up in most of the functions on the critical execution path. The insertion of Trace objects has slowed down performance by a factor of five.
We are talking about the case when tracing was off and performance was supposed to be unaffected. Function call overhead is a factor so we should inline short, frequently called functions.
Copying objects is expensive. Prefer pass-by-reference over pass-by-value. Our initial Trace implementation has adhered to all three of these principles. We stuck by the rules and yet we got blindsided. It is the creation and eventual destruction of unnecessary objects that were created in anticipation of being used but are not.
The Trace implementation is an example of the devastating effect of useless objects on performance, evident even in the simplest use of a Trace object. Invoke the Trace constructor. The Trace constructor invokes the string constructor to create the member string.
Invoke the Trace destructor. The Trace destructor invokes the string destructor for the member string. When tracing is off, the string member object never gets used.
You could also make the case that the Trace object itself is not of much use either when tracing is off. All the computational effort that goes into the creation and destruction of those objects is a pure waste. Keep in mind that this is the cost when tracing is off.
This was supposed to be the fast lane. So how expensive does it get? We are trying to isolate the performance factors one at a time. This is Version 1 see Figure 1. The performance cost of the Trace object. In other words, the speed of addOne has plummeted by a factor of more than This kind of overhead will wreak havoc on the performance of any software.
The cost of our tracing implementation was clearly unacceptable. We had to regroup and come up with a more efficient implementation. The Recovery Plan The performance recovery plan was to eliminate objects and computations whose values get dropped when tracing is off. We started with the string argument created by addOne and given to the Trace constructor.
Forget the string object. This translated into a performance boost, as was evident in our measurement. Execution time dropped from 3, ms to 2, ms see Figure 1. Impact of eliminating one string object. The second step is to eliminate the unconditional creation of the string member object contained within the Trace object. From a performance perspective we have two equivalent solutions. One is to replace the string object with a plain char pointer. The other solution is to use composition instead of aggregation.
Instead of embedding a string subobject in the Trace object, we could replace it with a string pointer. The advantage of a string pointer over a string object is that we can delay creation of the string after we have verified that tracing was on. Response time has dropped from 2, ms to ms see Figure 1. Impact of conditional creation of the string member. TE So we have arrived. We took the Trace implementation from 3, ms down to ms. You may still contend that ms looks pretty bad compared to a ms execution time when addOne had no tracing logic at all.
This is more than 3x degradation. So how can we claim victory? The point is that the original addOne function without trace did very little. It added one to its input argument and returned immediately. The addition of any code to addOne would have a profound effect on its execution time. If you add four instructions to trace the behavior of only two instructions, you have tripled your execution time.
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If addOne consisted of more complex computations, the addition of Trace would have been closer to being negligible. In some ways, this is similar to inlining. The influence of inlining on heavyweight functions is negligible.
Inlining plays a major role only for simple functions that are dominated by the call and return overhead. The functions that make excellent candidates for inlining are precisely the ones that are bad candidates for tracing. It follows that Trace objects should not be added to small, frequently executed functions. We call it "silent execution" as opposed to "silent overhead" because object construction and destruction are not usually overhead. If the computations performed by the constructor and destructor are always necessary, then they would be considered efficient code inlining would alleviate the cost of call and return overhead.
As we have seen, constructors and destructors do not always have such "pure" characteristics, and they can create significant overhead. However, it is seen less often in C because it lacks constructor and destructor support. Just because we pass an object by reference does not guarantee good performance.
Avoiding object copy helps, but it would be helpful if we didn't have to construct and destroy the object in the first place. Don't waste effort on computations whose results are not likely to be used. When tracing is off, the creation of the string member is worthless and costly.
Don't aim for the world record in design flexibility. All you need is a design that's sufficiently flexible for the problem domain. A char pointer can sometimes do the simple jobs just as well, and more efficiently, than a string.
Eliminate the function call overhead that comes with small, frequently invoked function calls. Inlining the Trace constructor and destructor makes it easier to digest the Trace overhead. Constructors and Destructors In an ideal world, there would never be a chapter dedicated to the performance implications of constructors and destructors. In that ideal world, constructors and destructors would have no overhead. They would perform only mandatory initialization and cleanup, and the average compiler would inline them.
That's the theory. Down here in the trenches of software development, the reality is a little different. We often encounter inheritance and composition implementations that are too flexible and too generic for the problem domain. They may perform computations that are rarely or never required. In practice, it is not surprising to discover performance overhead associated with inheritance and composition.
Inheritance and composition involve code reuse. Oftentimes, reusable code will compute things you don't really need in a specific scenario.
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Any time you call functions that do more than you really need, you will take a performance hit. Inheritance Inheritance and composition are two ways in which classes are tied together in an object-oriented design. In this section we want to examine the connection between inheritance-based designs and the cost of constructors and destructors. We drive this discussion with a practical example: the implementation of thread synchronization constructs.
Thread synchronization constructs appear in varied forms. The three most common ones are semaphore, mutex, and critical section. A semaphore provides restricted concurrency. It allows multiple threads to access a shared resource up to a given maximum. When the maximum number of concurrent threads is set to 1, we end up with a special semaphore called a mutex MUTual EXclusion.
A mutex protects shared resources by allowing one and only one thread to operate on the resource at any one time. A shared resource typically is manipulated in separate code fragments spread over the application's code. Take a shared queue, for example. The number of elements in the queue is manipulated by both enqueue and dequeue routines.
Modifying the number of elements should not be done simultaneously by multiple threads for obvious reasons. Modifying this variable must be done atomically. The simplest application of a mutex lock appears in the form of a critical section.
A critical section is a single fragment of code that should be executed only by one thread at a time. To achieve mutual exclusion, the threads must contend for the lock prior to entering the critical section.
The thread that succeeds in getting the lock enters the critical section. Upon exiting the critical section, the thread releases the lock to allow other threads to enter. In Win32, a critical section consists of one or more distinct code fragments of which one, and only one, can execute at any one time.
The difference between a critical section and a mutex in Win32 is that a critical section is confined to a single process, whereas mutex locks can span process boundaries and synchronize threads running in separate processes.
We are just pointing it out to avoid confusion. In practice we have seen routines that consisted of hundreds of lines of code containing multiple return statements. If a lock was obtained somewhere along the way, we had to release the lock prior to executing any one of the return statements. As you can imagine, this was a maintenance nightmare and a sure bug waiting to surface.
Large-scale projects may have scores of people writing code and fixing bugs. If you add a return statement to a line routine, you may overlook the fact that a lock was obtained earlier. That's problem number one. The second one is exceptions: If an exception is thrown while a lock is held, you'll have to catch the exception and manually release the lock.
Not very elegant. When an object reaches the end of the scope for which it was defined, its destructor is called automatically. You can utilize the automatic destruction to solve the lock maintenance problem. Encapsulate the lock in an object and let the constructor obtain the lock.
The destructor will release the lock automatically. If such an object is defined in the function scope 10 of a line routine, you no longer have to worry about multiple return statements. The compiler inserts a call to the lock destructor prior to each return statement and the lock is always released. A mutex allows only one thread to access a shared resource. Nesting Some constructs allow a thread to acquire a lock when the thread already holds the lock. Other constructs will deadlock on this lock-nesting.
Notify When the resource becomes available, some synchronization constructs will notify all waiting threads.
This is very inefficient as all but one thread wake up to find out that they were not fast enough and the resource has already been acquired. A more efficient notification scheme will wake up only a single waiting thread. To get the free app, enter your mobile phone number. Would you like to tell us about a lower price?
In most places examples are given with solutions. This book attempts to focus on the classroom teaching- learning sequence in a step by step manner, with example solving, which is a must for learning this subject. Read more Read less. Matchbook Price: Thousands of books are eligible, including current and former best sellers. Look for the site MatchBook icon on print and site book detail pages of qualifying books. Print edition must be downloadd new and sold by site.
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A Low-level language is specific to one machine, i. It is machine dependent, fast to run. But it is not easy to understand. A High-Level language is not specific to one machine, i. It is easy to understand. C Program In this tutorial, all C programs are given with C compiler so that you can quickly change the C program code. File: main.C Programming with Solved Problems. It grows with the number of data members that are initialized by the constructor. For example, if you want to create a wearable electronic project, you might want to consider the LilyPad board from Sparkfun.
The insertion of Trace objects has slowed down performance by a factor of five. Back to top. Chapter 3 gives the basis of control statements followed by chapter 4 which teaches advanced control statement. We refer to thread synchronization concepts in several other places in the book.
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