The Future of Parallel Computing

1-How is the molecular computer differs from any other manmade computer?

Like the brain but unlike other existing manmade computers, this new system can heal itself because the molecules that make up the computer can automatically reorganize themselves.

2-What are the challenges for all processors requirements?

1. Low cost

2. Low power consumption.

3. Availability of support for parallel programming.

4. Efficient porting of existing codes.

3-What is the future in GPGPU compared to GPU?

The GPU is faster, very faster compared to CPU because GPU is designed for special purposes (high graphics).

In future also we will see mature GPGPU frameworks GPGPU means General Purpose Graphic Processing Unit for everything not only the graphics.

4-How can we get the best use from extra cores that we will see in the future?

1-Programs must be parallelized. Multiple paths of execution have to work together to complete the tasks the program has to perform, and as much of that work as possible has to happen concurrently. Only then is it possible to speed up the program (i.e., reduce the total runtime).

2- Exploiting large-scale parallel hardware will be essential for improving the applications performance or its capabilities in terms of executing speed and power consumption.

The Future of Parallel Computing

1-How is the molecular computer differs from any other manmade computer?

Like thebrainbut unlike other existingmanmade computers, this new system can heal itself because the molecules that make up the computer can automatically reorganize themselves.

2-What are the challenges for all processors requirements?

1. Low cost

2. Low power consumption.

3. Availability of support for parallel programming.

4. Efficient porting of existing codes.

3-What is the future in GPGPU compared to GPU?

The GPU is faster, very faster compared to CPU because GPU is designed for special purposes (high graphics).

In future also we will see mature GPGPU frameworks

GPGPU means General Purpose Graphic Processing Unit for everything not only the graphics.

4-How can we get the best use from extra cores that we will see in the future?

1-Programs must be parallelized. Multiple paths of execution have to work together to complete the tasks the program has to perform, and as much of that work as possible has to happen concurrently. Only then is it possible to speed up the program (i.e., reduce the total runtime).

2- Exploiting large-scale parallel hardware will be essential for improving the applications performance or its capabilities in terms of executing speed and power consumption.