Adding a cache hierarchy, CGRA-specific runahead prefetching, and per-PE cache reconfiguration allows CGRAs to process irregular memory-access kernels at near-ideal speed with 1.27% of the storage.
Succinct Dynamic Ordered Sets with Random Access
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abstract
The representation of a dynamic ordered set of $n$ integer keys drawn from a universe of size $m$ is a fundamental data structuring problem. Many solutions to this problem achieve optimal time but take polynomial space, therefore preserving time optimality in the \emph{compressed} space regime is the problem we address in this work. For a polynomial universe $m = n^{\Theta(1)}$, we give a solution that takes $\textsf{EF}(n,m) + o(n)$ bits, where $\textsf{EF}(n,m) \leq n\lceil \log_2(m/n)\rceil + 2n$ is the cost in bits of the \emph{Elias-Fano} representation of the set, and supports random access to the $i$-th smallest element in $O(\log n/ \log\log n)$ time, updates and predecessor search in $O(\log\log n)$ time. These time bounds are optimal.
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Re-thinking Memory-Bound Limitations in CGRAs
Adding a cache hierarchy, CGRA-specific runahead prefetching, and per-PE cache reconfiguration allows CGRAs to process irregular memory-access kernels at near-ideal speed with 1.27% of the storage.