Function merging is an important optimization for reducing code size. This technique
eliminates redundant code across functions by merging them into a single function. While …

Resource-constrained devices for embedded systems are becoming increasingly important.
In such systems, memory is highly restrictive, making code size in most cases even more …

Function merging is an important optimization for reducing code size. It merges multiple
functions into a single one, eliminating duplicate code among them. The existing state-of-the …

Loop unrolling is a widely adopted loop transformation, commonly used for enabling
subsequent optimizations. Straight-line-code vectorization (SLP) is an optimization that …

Code size is critical for resource-constrained devices, where memory and storage are
limited. Compilers, therefore, should offer optimizations aimed at code reduction. One such …

Auto-vectorization techniques allow the compiler to automatically generate SIMD vector
code out of scalar code. SLP is a commonly-used algorithm for converting straight-line code …

SLP Auto-vectorization converts straight-line code into vector code. It scans input code for
groups of instructions that can be combined into vectors and replaces them with their …

Sparse computations, such as sparse matrix-dense vector multiplication, are notoriously
hard to optimize due to their irregularity and memory-boundedness. Solutions to improve the …

Currently, there are three vectorizers in the LLVM trunk: Loop Vectorizer, SLP Vectorizer,
and Load-Store Vectorizer. There is a need for vectorizing functions/kernels: 1) Function …

Leveraging the SIMD capability of modern CPU architectures is mandatory to take full
advantage of their increased performance. To exploit this capability, binary executables …