Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Semantic prefetching using forecast slices   Modern prefetchers identify memory access patterns in order to predict future
accesses. However, many applications exhibit irregular access patterns that do
not manifest spatio-temporal locality in the memory address space. Such
applications usually do not fall under the scope of existing prefetching
techniques, which observe only the stream of addresses dispatched by the memory
unit but not the code flows that produce them. Similarly, temporal correlation
prefetchers detect recurring relations between accesses, but do not track the
chain of causality in program code that manifested the memory locality.
Conversely, techniques that are code-aware are limited to the basic program
functionality and are bounded by the machine depth. In this paper we show that
contextual analysis of the code flows that generate memory accesses can detect
recurring code patterns and expose their underlying semantics even for
irregular access patterns. Moreover, program locality artifacts can be used to
enhance the memory traversal code and predict future accesses. We present the
semantic prefetcher that analyzes programs at run-time and learns their memory
dependency chains and address calculation flows. The prefetcher then constructs
forecast slices and injects them at key points to trigger timely prefetching of
future contextually-related iterations. We show how this approach takes the
best of both worlds, augmenting code injection with forecast functionality and
relying on context-based temporal correlation of code slices. This combination
allows us to overcome critical memory latencies that are currently not covered
by any other prefetcher. Our evaluation of the semantic prefetcher using an
industrial-grade, cycle-accurate x86 simulator shows that it improves
performance by 24% on average over SPEC 2006 (outliers up to 3.7x), and 16% on
average over SPEC 2017 (outliers up to 1.85x), using only ~6KB.

25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
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The categories of this paper are: adap-org
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The categories of this paper are: q-fin
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The categories of this paper are: math-ph
19
The categories of this paper are: eess
10
The categories of this paper are: q-bio
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The categories of this paper are: nucl-th
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The categories of this paper are: plasm-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: q-alg