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High Performance Fortran (HPF) is a programming language derived from Fortran, specifically designed for high-performance computing. Developed in the early 1990s, HPF introduces extensions to handle operations on aggregate data structures such as arrays. It includes features that allow developers to specify parallelism explicitly and implicitly, which makes it suitable for use on parallel computing systems. HPF contains directives for data distribution across different processors of a parallel machine. This allows programmers to control how computations are divided among various processing elements and reduces the complexity involved in writing distributed-memory programs. Despite its strengths, HPF has been criticized for its lack of support for dynamic load balancing and complex communication patterns. Its popularity declined with the rise of other parallel programming paradigms like MPI (Message Passing Interface) and OpenMP. Overall, while not widely used today, High Performance Fortran played an important role in the history of high-performance and scientific computing by providing a way to write portable code that could efficiently exploit parallel architectures.

Ask the right questions secure the right HPF talent among an increasingly shrinking pool of talent.

First 20 minutes

General HPF app knowledge and experience

The first 20 minutes of the interview should seek to understand the candidate's general background in HPF application development, including their experience with various programming languages, databases, and their approach to designing scalable and maintainable systems.

What are the basic components of HPF?

The basic components of HPF are directives, library procedures, and language extensions.

How would you explain the concept of data parallelism in HPF?

Data parallelism in HPF is a paradigm where a large amount of data is divided into smaller units and processed in parallel.

Describe the difference between distributed and shared memory in HPF.

Distributed memory in HPF refers to data being spread across different processors with each having its own memory. Shared memory refers to a memory accessible by all processors.

What are the types of data distribution in HPF?

The types of data distribution in HPF are block distribution, cyclic distribution, and block-cyclic distribution.

How would you handle exceptions in HPF?

Exceptions in HPF can be handled using the ON directive which allows specification of error handling procedures.

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What you’re looking for early on

Does the candidate have a solid understanding of HPF?

Has the candidate demonstrated problem-solving skills?

Is the candidate able to communicate effectively?

Does the candidate have experience with other relevant technologies?

Next 20 minutes

Specific HPF development questions

The next 20 minutes of the interview should focus on the candidate's expertise with specific backend frameworks, their understanding of RESTful APIs, and their experience in handling data storage and retrieval efficiently.

What is the purpose of the FORALL statement in HPF?

The FORALL statement in HPF is used for concurrent execution of statements without side effects.

What is the role of the REDISTRIBUTE directive in HPF?

The REDISTRIBUTE directive in HPF is used to change the distribution format of an existing distributed array.

How would you use the ALIGN directive in HPF?

The ALIGN directive in HPF is used to align elements of one distributed array with elements of another.

Describe the difference between the INHERIT and the INDEPENDENT directives in HPF.

The INHERIT directive in HPF allows a variable to inherit the distribution of another variable, while the INDEPENDENT directive specifies that iterations of a loop are independent and can be executed in any order.

How would you optimize performance in HPF?

Performance in HPF can be optimized by carefully choosing the data distribution and aligning the data properly to minimize communication overhead.

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At this point, a skilled HPF engineer should demonstrate strong problem-solving abilities, proficiency in HPF programming language, and knowledge of software development methodologies. Red flags include lack of hands-on experience, inability to articulate complex concepts, or unfamiliarity with standard coding practices.

Digging deeper

Code questions

These will help you see the candidate's real-world development capabilities with HPF.

What does the following HPF code do?
REAL, DIMENSION(10,10) :: A, B, C
!HPF$ INDEPENDENT, NEW(B)
DO I=1,10
  DO J=1,10
    A(I,J) = B(I,J) + C(I,J)
  END DO
END DO
This code adds the elements of two 10x10 matrices B and C and stores the result in matrix A. The 'INDEPENDENT, NEW(B)' directive allows the compiler to execute the loop iterations in any order, potentially in parallel, because there are no dependencies between iterations.
What will be the output of the following HPF code?
INTEGER, DIMENSION(5) :: A = (/1, 2, 3, 4, 5/)
PRINT *, A(3)
The output will be '3'. This code declares an array A of size 5 and initializes it with the values 1 through 5. It then prints the third element of the array, which is 3.
What does the following HPF code do?
INTEGER, DIMENSION(10) :: A = (/1, 2, 3, 4, 5, 6, 7, 8, 9, 10/)
!HPF$ INDEPENDENT
DO I=1,10
  A(I) = A(I) * 2
END DO
PRINT *, A
This code multiplies each element of the array A by 2. The 'INDEPENDENT' directive allows the compiler to execute the loop iterations in any order, potentially in parallel, because there are no dependencies between iterations. The final line prints the modified array.
What does the following HPF code do?
!HPF$ PROCESSORS P(4)
REAL, DIMENSION(10) :: A
!HPF$ DISTRIBUTE A(BLOCK) ONTO P
This code declares a processor arrangement P with 4 processors and an array A of size 10. It then distributes the elements of A in blocks onto the processors in P. This means that each processor gets a contiguous block of elements from A.

Wrap-up questions

Final candidate for HPF Developer role questions

The final few questions should evaluate the candidate's teamwork, communication, and problem-solving skills. Additionally, assess their knowledge of microservices architecture, serverless computing, and how they handle HPF application deployments. Inquire about their experience in handling system failures and their approach to debugging and troubleshooting.

What is the purpose of the PROCESSORS directive in HPF?

The PROCESSORS directive in HPF is used to declare a processor arrangement.

Describe the difference between the BLOCK and CYCLIC distributions in HPF.

BLOCK distribution in HPF assigns contiguous blocks of array elements to processors while CYCLIC distribution assigns elements in a round-robin fashion.

How would you use the REALIGN directive in HPF?

The REALIGN directive in HPF is used to change the alignment of an existing distributed array.

HPF application related

Product Perfect's HPF development capabilities

Beyond hiring for your HPF engineering team, you may be in the market for additional help. Product Perfect provides seasoned expertise in HPF projects, and can engage in multiple capacities.

HPF Consultive assessments

HPF Application Conversion Assessment HPF Application Integration Assessment HPF Data & Database Integration Assessment

Custom HPF development projects

Custom HPF App Conversion HPF Custom App Development Process App UI Design for HPF Facelifts

Hiring guide for HPF Engineers

HPF Developer Hiring Guide

What you’re looking for early on

The ideal back-end app developer

What you’re looking to see on the HPF engineer at this point.

HPF Consultive assessments

Custom HPF development projects