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Traditional Von Neumann computing is falling apart in the era of exploding data volumes as the overhead of data transfer becomes forbidding. Instead, it is more energy-efficient to fuse compute capability with memory where the data reside. This is particularly critical for pattern matching, a key computational step in large-scale data analytics, which involves repetitive search over very large databases residing in memory. Emerging spintronic technologies show remarkable versatility for the tight integration of logic and memory. In this paper, we introduce CRAM-PM, a novel high-density, reconfigurable spintronic in-memory compute substrate for pattern matching.
Recent architectural approaches that address speculative side-channel attacks aim to prevent software from exposing the microarchitectural state changes of transient execution. The Delay-on-Miss technique is one such approach, which simply delays loa
Bipartite b-matching is fundamental in algorithm design, and has been widely applied into economic markets, labor markets, etc. These practical problems usually exhibit two distinct features: large-scale and dynamic, which requires the matching algor
It has always been difficult to balance the accuracy and performance of ISSs. RTL simulators or systems such as gem5 are used to execute programs in a cycle-accurate manner but are often prohibitively slow. In contrast, functional simulators such as
The problem of matching a query string to a directed graph, whose vertices are labeled by strings, has application in different fields, from data mining to computational biology. Several variants of the problem have been considered, depending on the
Genomics is the foundation of precision medicine, global food security and virus surveillance. Exact-match is one of the most essential operations widely used in almost every step of genomics such as alignment, assembly, annotation, and compression.