Both Phi and CUDA are great coprocessors. They have been in the market for quite a long time. They give a great level of parallelism. This two have been in a slight competition, even if the competition exists mainly amongst the users, a constant comparison is done between these two. There has been attempt of doing programs in CUDA applications that can run smoothly on the Phi processor. Things have been good so far. Further development is expected and tests are being conducted regarding the purpose.

The CUDA and Phi programming can be better understood if a little comparative study is held on this two. The famous company Intel has implemented Phi in designing processors. The Intel 60core Phi processor is designed to work as the basic x86 architecture with some technical extensions. This was the fast major application of Phi in the Intel family. There is a scope for a massive parallelism and also a 512 bit per code vector unit. These small technical specifications affect the performance of the processor and make it very useful. The CUDA applications are compatible with the Phi coprocessor. This is great news for every tech savvy person.

The Intel Xeon Phi is the next development. This coprocessor provides great performance with huge megaflops. The small technicalities that are available on this coprocessor are very impressive. The technicalities may not be clear to all but its affect on the performance is very critical and easily noticeable. The floating point performance can be amplified using pragmas. There are other ways of increasing the performance that require a little more detailed study to understand. SMP or Symmetric Multi Processor plays an important part in this concept as well as MPI nodes. These are some of the technical details of the Phi processors.

The Phi processors support programs and applications on many varieties of languages. CUDA is one of the programming aspects that are compatible with Phi processor. CUDA programming model is very significant in the development of Phi processor. When handled carefully and with lots of precision, CUDA model is very accurate in functioning with Phi processor. The number of threads and parallelisms of great significance of thinking of combining the CUDA with Phi. CUDA programming needs to be in sync with the Message passing Interface or MSI. Offload mode of Phi processor can also prove to be very useful while using CUDA on Phi processor.

There are many technicalities of CUDA programs in Phi processor. There are some benefits and some drawbacks. There are some limitations of this, one of which is the memory capacity. This is going to be of more concern while running SMP or MPI applications. There are some tools and software that can help in porting CUDA codes to Phi processors. These tools and software are very important when working in the offload model of programming. Some modifications are required. Some changes are already implemented and some are still in the planning stage. It is a great possibility that this combination will be smoother and more accurate in future.