  Due to the proliferation of spatial light modulators, digital holography is
finding wide-spread use in fields from augmented reality to medical imaging to
additive manufacturing to lithography to optical tweezing to
telecommunications. There are numerous types of SLM available with a multitude
of algorithms for generating holograms. Each algorithm has limitations in terms
of convergence speed, power efficiency, accuracy and data storage requirement.
  Here, we consider probably the most common algorithm for computer generated
holography - Gerchberg-Saxton - and examine the trade-off in convergent
quality, performance and efficiency. In particular, we focus on measuring and
understanding the factors that control runtime and convergence.
