We present an interdisciplinary study to tackle the memory bottleneck of training deep
convolutional neural networks (CNN). Firstly, we introduce Split Convolutional Neural …

Stencil computation is an indispensable building block of many scientific applications and is
widely used by the numerical solvers of partial differential equations (PDEs). Due to the …

В работе рассматриваются преобразования программ, приводящие к ускорению.
Приводятся публикации о различных параллельных вычислительных архитектурах и …

Stencil computations represent a very common class of nested loops in scientific and
engineering applications. The exhaustively studied tiling is one of the most powerful …

The advantages of the second-generation AMD EPYC Rome processors can be
successfully used in the race to Exascale. However, the novel architecture's complexity …

We propose a new notation for data parallel operators on multi-dimensional arrays named
tensor comprehensions. This notation combines the basic principle of array …

Loop tiling is a key high-level transformation which is known to maximize locality in loop
intensive programs. It has been successfully applied to a number of applications including …

Stencil is one of the indispensable computation patterns in scientific applications, which is a
long-standing optimization target in the field of high performance computing (HPC). The …

An overview of the most prominent contemporary parallel processing programming models,
written in a unique tutorial style. With the coming of the parallel computing era, computer …

Stencil computations expose a large and complex space of equivalent implementations.
These computations often rely on autotuning techniques, based on iterative compilation or …