In the simplest sense, parallel computing is the simultaneous use of multiple co
ID: 3920621 • Letter: I
Question
In the simplest sense, parallel computing is the simultaneous use of multiple compute resources to solve a computational problem. A problem is broken into parts that can be concurrently solved. Each part is broken down to a series of instructions. Instructions from each part execute simultaneously on different processors, and an overall coordination is utilized. What is the difference between the parallel computing nowadays and a decade ago? How is it implemented now and then? Search online and report back the improvements of the Windows operating system after using the parallel computing. In addition, research and report back the tradeoffs of the parallel computing done in hardware vs software.
Please provice more than 300 words
Explanation / Answer
Answer :
The main difference is that the hardware itself is highly parallelized. A few decades ago, parallelism was more "simulated" at the operating system level, and multitasking on hardware was basically not parallel. Therefore, there are many processes for different users on a multi-user system, but parallelism occurs through context switching. Over the years, much research has been done on optimizing context switching techniques, and single core CPUs have been optimized to minimize context switching overhead.
CPUs are usually composed of multi-core technology, and in the mid-2000s, most CPUs were single-core. There is now a new Moores rule, just like the extension of the CPU kernel. A useful scientific reference that helps conceptualize and understand the historical "paradigm shift" of parallel processing of CPUs and other hardware is the prospect of parallel computing.
Improvements of the Windows operating system:-
Parallel processing in windows introduced with window 7.Win32 was never designed for highly concurrent, asynchronous processing,". Improvements are done in windows through parallel processing are ; -
Hardware parallelism vs Software parallelism:
Hardware parallelism: Example - no. of processors
A multiprocessor system with an xn-issue processor can handle the maximum limit of n parallel threads at xn parallel instructions or thread level parallel (TLP) levels.
Software parallelism : Example- Degree of Parallelism or number of parallel tasks at selected task or grain size.