What is BSP in machine learning?

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What is BSP in machine learning?

The bulk synchronous parallel (BSP) is a celebrated synchronization model for general-purpose parallel computing that has successfully been employed for distributed training of machine learning models. A prevalent shortcoming of the BSP is that it requires workers to wait for the straggler at every iteration.

What is parallel reduction?

One common approach to this problem is parallel reduction. This can be applied for many problems, a min operation being just one of them. The number of threads is then reduced by half and the process repeated until there is just a single element remaining, which is the result of the operation. …

What are the different types of PRAM?

Different Types of Prams and Strollers Available in the Market

  • Prams.
  • Strollers.
  • Standard Strollers.
  • Lightweight Strollers.
  • Jogging Strollers.
  • Travel Systems.
  • Double Strollers.
  • Stroller Frames.
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What is parallel reduction Cuda?

Parallel reduction algorithm typically refers to an algorithm which combines an array of elements, producing a single result. Typical problems that fall into this category are: summing up all elements in an array. finding a maximum in an array.

What is a reduction operation?

To start with the basics: a reduction operation takes a function that takes two arguments – an accumulator and the current iteration. With each iteration it combines these two arguments into a single value which is then put into the accumulator for the next iteration to use.

What is the bulk synchronous parallel model?

The bulk synchronous parallel (BSP) model was developed by Leslie Valiant in the 1980s. The BSP model is intended as a bridging model between parallel hardware and software. It is an elegant and simple model that has a small and easy to understand interface. The BSP model is defined on an abstract computer called a BSP computer.

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What is a BSP abstract computer?

The bulk synchronous parallel (BSP) abstract computer is a bridging model for designing parallel algorithms. It is similar to the parallel random access machine (PRAM) model, but unlike PRAM, BSP does not take communication and synchronization for granted.

When was the Multi-BSP model published?

Valiant developed an extension to the BSP model in the 2000s, leading to the publication of the Multi-BSP model in 2011. In 2017, McColl developed a major new extension of the BSP model that provides fault tolerance and tail tolerance for large-scale parallel computations in AI, Analytics and high-performance computing (HPC).

What is an example of decomposable BSP?

One example of this is the decomposable BSP model. The model has also been used in the creation of a number of new programming languages and interfaces, such as Bulk Synchronous Parallel ML (BSML), BSPLib, Apache Hama, and Pregel.

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