A prefetching technique for irregular accesses to linked data structures

Karlsson, Magnus; Dahlgren, Fredrik; Stenström, Per

doi:10.1109/hpca.2000.824351

Cited by 53 publications

(61 citation statements)

References 21 publications

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“…Previous approaches that use static analysis to predict access to persistent data have targeted specific types of data structures such as linked data structures [1,3,7], recursive data structures [10,13] or matrices [12]. To the best of our knowledge, our work is the first that predicts access to persistent objects of any type prior to application execution.…”

Section: Related Workmentioning

confidence: 90%

Predicting Access to Persistent Objects Through Static Code Analysis

Touma

Queralt

Cortes

et al. 2017

Communications in Computer and Information Science

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Abstract. In this paper, we present a fully-automatic, high-accuracy approach to predict access to persistent objects through static code analysis of object-oriented applications. The most widely-used previous technique uses a simple heuristic to make the predictions while approaches that offer higher accuracy are based on monitoring application execution. These approaches add a non-negligible overhead to the application's execution time and/or consume a considerable amount of memory. By contrast, we demonstrate in our experimental study that our proposed approach offers better accuracy than the most common technique used to predict access to persistent objects, and makes the predictions farther in advance, without performing any analysis during application execution.

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Section: Related Workmentioning

confidence: 90%

Predicting Access to Persistent Objects Through Static Code Analysis

Touma

Queralt

Cortes

et al. 2017

Communications in Computer and Information Science

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“…By issuing a prefetch instruction before other work is done in a loop, memory latency caused by a cache-miss on a pointer traversal can be hidden, provided that the work done in the loop body is substantial. Karlsson et al [19] describe techniques to prefetch irregular accessed linked structures which extends the work of Luk and Mowry [24], who mention data linearization as a technique to improve prefetching efficiency and locality. Yang and Lebeck [33] present a memory architecture which pro-actively dereferences pointers lower in the hierarchy to push data higher into the memory hierarchy instead of waiting for the higher memory-level to pull the data.…”

Section: Related Workmentioning

confidence: 96%

A Compile/Run-time Environment for the Automatic Transformation of Linked List Data Structures

Spek

Groot

Bakker

et al. 2008

Int J Parallel Prog

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Irregular access patterns are a major problem for today's optimizing compilers. In this paper, a novel approach will be presented that enables transformations that were designed for regular loop structures to be applied to linked list data structures. This is achieved by linearizing access to a linked list, after which further data restructuring can be performed. Two subsequent optimization paths will be considered: annihilation and sublimation, which are driven by the occurring regular and irregular access patterns in the applications. These intermediate codes are amenable to traditional compiler optimizations targeting regular loops. In the case of sublimation, a run-time step is involved which takes the access pattern into account and thus generates a data instance specific optimized code. Both approaches are applied to a sparse matrix multiplication algorithm and an iterative solver: preconditioned conjugate gradient. The resulting transformed code is evaluated using the major compilers for the x86 platform, GCC and the Intel C compiler.

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“…One way to categorize prefetching schemes is based on the data access patterns that they target. Hence, they can be broadly classi ed as sequential 33], strided 9, 14, 19], streamed 16,21,32], data-dependency based 28], pointer based 22,25,29], and address-correlation based 8,20,24]. Since our focus is on strided accesses, we compare our scheme with the other approaches to stride prefetching in the rest of this section.…”

Section: Related Workmentioning

confidence: 99%

Profile-guided post-link stride prefetching

Luk

Muth

Patil

et al. 2002

Proceedings of the 16th International Conference on Supercomputing

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Data prefetching is an e ective approach to addressing the memory latency problem. While a few processors have i mplemented hardware-based data prefetching, the majority o f modern processors support data-prefetch instructions and rely on compilers to automatically insert prefetches. However, most prefetching schemes in commercial compilers suffer from two limitations: (1) the source code must be available before prefetching can be applied, and (2) these prefetching schemes target only loops with statically-known strided accesses. In this study, w e broaden the scope of softwarecontrolled prefetching by addressing the above t wo limitations. We use pro ling to discover strided accesses that frequently occur during program execution but are not determinable by the compiler. We then use the strides discovered to insert prefetches into the executable directly, without the need for re-compilation. Performance evaluation was done on an Alpha 21264-based system with a 64KB data cache and an 8MB secondary cache. We nd that even with such large caches, our technique o ers speedups ranging from 3% to 56% in 11 out of the 26 SPEC2000 benchmarks. Our technique has been incorporated into Pixie and Spike, t wo products in Compaq's Tru64 Unix.

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A prefetching technique for irregular accesses to linked data structures

Abstract: Prefetching offers the potential to improve the performance of linked data structure (LDS) traversals. However, previously

Cited by 53 publications

References 21 publications

Predicting Access to Persistent Objects Through Static Code Analysis

Predicting Access to Persistent Objects Through Static Code Analysis

A Compile/Run-time Environment for the Automatic Transformation of Linked List Data Structures

Profile-guided post-link stride prefetching

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