The advantages of being able to solve a problem faster often outweighs the cost of investing in parallel computing hardware.I am doing performance tests on an algorithm I wrote for parallel matrix multiplication in Java. In many industries, the time saved using parallel computing also leads to saving money. Web search engines that process millions of transactions every second are only possible thanks to parallel computing. Some computing problems are so large or complex, that it's not practical or even possible to solve them with a single computer. But that extra work can be worth the extra effort, because when done right, parallel execution increases the overall throughput of a program, enabling us to break down large tasks to accomplish them faster or to accomplish more tasks in a given amount of time. Those coordination challenges are part of what make writing parallel programs harder than simple sequential programs. And there might be times when one of us has to wait for the other cook to finish a certain step before we continue on. We have to spend extra effort to communicate with each other to coordinate our actions. Adding a second cook in the kitchen doesn't necessarily mean we'll make the salad twice as fast, because adding extra cooks in the kitchen adds complexity. By working together in parallel, it only took us two minutes to make the salad, which is faster than the three minutes it took Barron to do it alone. So we had to coordinate with each other for that step. That final step of adding dressing was dependent on all of the previous steps being done. While I was slicing cucumbers and onions, Barron was chopping lettuce and tomatoes. Working together, we broke the recipe into independent parts that can be executed simultaneously by different processors. (knives chopping and slicing) - And finally, I'll add some dressing. (knives chopping and slicing) - And when I'm done chopping lettuce, I'll slice the tomatoes. While I chop the lettuce, - I'll slice the cucumber. Now we can break down the salad recipe and execute some of those steps in parallel. Two cooks in the kitchen represent a system with multiple processors. That's my personal speed record and I can't make a salad any faster than that without help. Each step takes some amount of time and in total, it takes me about three minutes to execute this program and make a salad. I'll slice and chop ingredients as fast as I can, but there's a limit to how quickly I can complete all of those tasks by myself.
#SEQUENTIAL PROGRAM FASTER THAN PARALLEL SERIES#
The time it takes for a sequential program to run is limited by the speed of the processor and how fast it can execute that series of instructions. And it's how new programmers are usually taught to code, because it's easy to understand, but it has its limitations.
#SEQUENTIAL PROGRAM FASTER THAN PARALLEL SERIAL#
This type of serial or sequential programming is how software has traditionally been written. And I can only execute one instruction at any given moment. The program is broken down into a sequence of discrete instructions that I execute one after another. As a single cook working alone in the kitchen, I'm a single processor, executing this program in a sequential manner. (knife slicing) And finally, I add the dressing. (knife slicing) I'll try not to cry while I slice the onion. (knife slicing) Next, I'll slice and add a few chunks of tomato. (knife chopping) Then I'll slice up a cucumber and add it.
So to execute the program, or recipe, to make a salad, I'll start by chopping some lettuce and putting it on a plate. Like a computer, I simply follow those instructions to execute the program. Like the steps in a recipe that tell me what to do when I'm cooking. A computer program is just a list of instructions that tells a computer what to do. Why it's worth the extra effort to write parallel code. Let's start by looking at what parallel computing means and why it's useful.
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