A Time-Predictable Object Cache

Abstract-To avoid data cache trashing between heapallocated data and other data areas, a distinct object cache has been proposed for embedded real-time Java processors. This object cache uses high associativity in order to statically track different object pointers for worst-case execution-time analysis. However, before implementing such an object cache, an empirical analysis of different organization forms is needed. We use a cross-profiling technique based on aspect-oriented programming in order to evaluate different object cache organizations with standard Java benchmarks. From the evaluation we conclude that field access exhibits some temporal locality, but almost no spatial locality. Therefore, filling long cache lines on a miss just introduces a high miss penalty without increasing the hit rate enough to make up for the increased miss penalty. For an object cache, it is more efficient to fill individual words within the cache line on a miss.

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“…More details of a concrete implementation of the object cache can be found in a complementary paper [14].…”

Section: The Object Cachementioning

confidence: 99%

“…The addresses of the objects, which is the input for standard cache analysis, are only known at runtime. As a solution to this issue, an object cache with high associativity has been proposed [14]. The cache content is tracked with symbolic addresses, employing a least-recently used or first-in first-out replacement policy.…”

Section: Introductionmentioning

confidence: 99%

Design Space Exploration of Object Caches with Cross-Profiling

Schoeberl

Binder

Villazón

2011

2011 14th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing

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“…Besides the fully associative single word cache we have implemented an object cache, further optimized for the object layout of JOP [38]. The object cache is organized to cache whole objects in a cache line.…”

Section: Object Cachementioning

confidence: 99%

Data cache organization for accurate timing analysis

2012

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Caches are essential to bridge the gap between the high latency main memory and the fast processor pipeline. Standard processor architectures implement two first-level caches to avoid a structural hazard in the pipeline: an instruction cache and a data cache. For tight worst-case execution times it is important to classify memory accesses as either cache hit or cache miss. The addresses of instruction fetches are known statically and static cache hit/miss classification is possible for the instruction cache. The access to data that is cached in the data cache is harder to predict statically. Several different data areas, such as stack, global data, and heap allocated data, share the same cache. Some addresses are known statically, other addresses are only known at runtime. With a standard cache organization all those different data areas must be considered by worst-case execution time analysis. In this paper we propose to split the data cache for the different data areas. Data cache analysis can be performed individually for the different areas. Access to an unknown address in the heap does not destroy the abstract cache state for other data areas. Furthermore, we propose to use a small, highly associative cache for the heap area. We designed and implemented a static analysis for this cache, and integrated it into a worst-case execution time analysis tool.

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“…This feature simplifies the low-level part of WCET analysis, a mandatory analysis for hard real-time systems. [47] and object cache [53], the extension module for hardware accelerators, and a scratchpad memory. Main memory and I/O devices are connected via the SimpCon interface to the CPU core.…”

Section: Java Optimized Processor (Jop)mentioning

confidence: 99%

“…It is argued that a split-cache design can simplify WCET analysis of data caches [52]. For heap allocated objects a time-predictable object cache has been implemented in JOP [53]. The object cache is organized to cache single objects in a cache line.…”

Section: Cache Organizations For Javamentioning

confidence: 99%