This article combines two practical approaches to improve pointer synthesis within HLS tools. Both approaches
focus on inefficiencies in how HLS tools treat the points-to graph – a mapping that connects each instruction to
the memory locations that it might access at runtime. HLS pointer synthesis first compute the points-to graph
via pointer analysis and then implements its connections in hardware, which gives rise to two inefficiencies.
Firstly, HLS tools typically favour pointer analysis that is fast, sacrificing precision. Secondly, they also favour
centralising memory connections in hardware for instructions that can point to more than one location.
In this article, we demonstrate that a more precise pointer analysis coupled with decentralised memory
connections in hardware can substantially reduce the unnecessary sharing of memory resources. We implement
both flow- and context-sensitive pointer analysis and fine-grained memory connections in two modern HLS
tools, LegUp and Vitis HLS. An evaluation on three benchmark suites, ranging from non-trivial pointer use
to standard HLS benchmarks, indicates that when we improve both precision and granularity of pointer
synthesis, on average, we can reduce area and latency by around 42% and 37% respectively.