  As spatial and temporal resolutions of scientific instruments improve, the
explosion in the volume of data produced is becoming a key challenge. It can be
a critical bottleneck for integration between scientific instruments at the
edge and high-performance computers/emerging accelerators. Placing data
compression or reduction logic close to the data source is a possible approach
to solve the bottleneck. However, the realization of such a solution requires
the development of custom ASIC designs, which is still challenging in practice
and tends to produce one-off implementations unusable beyond the initial
intended scope. Therefore, as a feasibility study, we have been investigating a
design workflow that allows us to explore algorithmically complex hardware
designs and develop reusable hardware libraries for the needs of scientific
instruments at the edge. Our vision is to cultivate our hardware development
capability for streaming/dataflow hardware components that can be placed close
to the data source to enable extreme data-intensive scientific experiments or
environmental sensing. Furthermore, reducing data movement is essential to
improving computing performance in general. Therefore, our co-design efforts on
streaming hardware components can benefit computing applications other than
scientific instruments. This vision paper discusses hardware specialization
needs in scientific instruments and briefly reviews our progress leveraging the
Chisel hardware description language and emerging open-source hardware
ecosystems, including a few design examples.
