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Andres Goens

Publications and source records attributed to Andres Goens.

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Automated Synthesis of Heterogeneous, Hierarchical, Scoped Coherence Protocols

Processor design is converging on a new model of cache-coherent shared memory characterized by heterogeneity, hierarchy, and scopes. Protocols like CXL or AMBA CHI are used as global protocols to combine multiple clusters, each with its own cluster-level coherence protocols. Manually designing shims to interface between these cluster and global protocols is subtle and error-prone. Automatic synthesis, on the other hand, makes simplifying assumptions like the single-writer multiple-reader (SWMR) invariant, that sacrifice performance for simplicity and guaranteed correctness. We present a shim API \textemdash a generic abstraction that enables us to classify protocol transactions by their semantic coherence guarantees. Our automated synthesis engine, ShimGen, uses this shim API to automatically compose protocols with both SWMR and relaxed accesses, taking advantage of modern architectural optimizations like scoped memory accesses and lazy invalidation. We demonstrate ShimGen's efficacy on two case studies. First, we compare its output to a manually-designed hierarchical protocol for the AMD APU released in gem5. ShimGen's output is similar to the existing protocol. However, we identify one scenario where the manually-designed protocol fails to uphold compound consistency, while ShimGen's does. Second, we compare the performance of a hierarchical protocol with a global protocol that exploits non-SWMR accesses to a hierarchical protocol with a strictly SWMR global protocol. The result shows the performance benefits of accommodating global protocols with non-SWMR behavior.

cs.AR

Generalized Data Placement Strategies for Racetrack Memories

Ultra-dense non-volatile racetrack memories (RTMs) have been investigated at various levels in the memory hierarchy for improved performance and reduced energy consumption. However, the innate shift operations in RTMs hinder their applicability to replace low-latency on-chip memories. Recent research has demonstrated that intelligent placement of memory objects in RTMs can significantly reduce the amount of shifts with no hardware overhead, albeit for specific system setups. However, existing placement strategies may lead to sub-optimal performance when applied to different architectures. In this paper we look at generalized data placement mechanisms that improve upon existing ones by taking into account the underlying memory architecture and the timing and liveliness information of memory objects. We propose a novel heuristic and a formulation using genetic algorithms that optimize key performance parameters. We show that, on average, our generalized approach improves the number of shifts, performance and energy consumption by 4.3x, 46% and 55% respectively compared to the state-of-the-art.

cs.DC

Achieving Determinism in Adaptive AUTOSAR

AUTOSAR Adaptive Platform is an emerging industry standard that tackles the challenges of modern automotive software design, but does not provide adequate mechanisms to enforce deterministic execution. This poses profound challenges to testing and maintenance of the application software, which is particularly problematic for safety-critical applications. In this paper, we analyze the problem of nondeterminism in AP and propose a framework for the design of deterministic automotive software that transparently integrates with the AP communication mechanisms. We illustrate our approach in a case study based on the brake assistant demonstrator application that is provided by the AUTOSAR consortium. We show that the original implementation is nondeterministic and discuss a deterministic solution based on our framework.

cs.DC