Yes, a lot of innovation had to occur to make the GraphBLAS linear algebra model practical, which has been in the works for more than 10 years. It began with Jeremy Kepner and John Gilbert's work formalizing the linear algebra model over semi-rings [1]. And then working with Intel, IBM, Nvidia and the other hardware vendors to define and implement a standard set of hardware primitives. But you could really see the stars align a few years ago then when the deep-learning ML wave hit because it paved the way with a surge in demand for GPU/TPU accelerators in the data center. A lot of things had to happen in to make this all come together. It's been an industry-wide effort.

[1] Graph Algorithms in the Language of Linear Algebra, by Jeremy Kepner and John Gilbert https://epubs.siam.org/doi/book/10.1137/1.9780898719918