Researcher:
Laghari, Mohammad

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PhD Student

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Mohammad

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Laghari

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Laghari, Mohammad

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2017 - 20183

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Researcher Of Publications: search.filters.isAuthorOfPublication.288df484-a3a5-4155-8a69-ac718501f63b

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    Object placement for high bandwidth memory augmented with high capacity memory
    (IEEE, 2017) N/A; N/A; Department of Computer Engineering; Laghari, Mohammad; Erten, Didem Unat; Master Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 219274
    High bandwidth memory (HBM) is a new emerging technology that aims to improve the performance of bandwidth limited applications. Even though it provides high bandwidth, it must be augmented with DRAM to meet the memory capacity requirement of any applications. Due to this limitation, objects in an application should be optimally placed on the heterogeneous memory subsystems. In this study, we propose an object placement algorithm that places program objects to fast or slow memories in case the capacity of fast memory is insufficient to hold all the objects to increase the overall application performance. Our algorithm uses the reference counts and type of references (read or write) to make an initial placement of data. In addition, we perform various memory bandwidth benchmarks to be used in our placement algorithm on Intel Knights Landing (KNL) architecture. Not surprisingly high bandwidth memory sustains higher read bandwidth than write bandwidth, however, placing write-intensive data on HBM results in better overall performance because write-intensive data is punished by the DRAM speed more severely compared to read intensive data. Moreover, our benchmarks demonstrate that if a basic block makes references to both types of memories, it performs worse than if it makes references to only one type of memory in some cases. We test our proposed placement algorithm with 6 applications under various system configurations. By allocating objects according to our placement scheme, we are able to achieve a speedup of up to 2x.
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    Phase-based data placement scheme for heterogeneous memory systems
    (IEEE, 2018) N/A; N/A; N/A; Department of Computer Engineering; Laghari, Mohammad; Ahmad, Najeeb; Erten, Didem Unat; PhD Student; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 219274
    Heterogeneous memory systems are equipped with two or more types of memories, which work in tandem to complement the capabilities of each other. The multiple memories can vary in latency, bandwidth and capacity characteristics across systems and they come in various configurations that can be managed by the programmer. This introduces an added programming complexity for the programmer. In this paper, we present a dynamic phase-based data placement scheme to assist the programmer in making decisions about program object allocations. We devise a cost model to assess the benefit of having an object in one type of memory over the other and apply the cost model at every application phase to capture the dynamic behaviour of an application. Our cost model takes into account the reference counts of objects and incurred transfer overhead when making a suggestion. In addition, objects can be transferred across memories asynchronously between phases to mask some of the transfer overhead. We test our cost model with a diverse set of applications from NAS Parallel and Rodinia benchmarks and perform experiments on Intel KNL, which is equipped with a high bandwidth memory (MCDRAM) and a high capacity memory (DDR). Our dynamic phase-based data placement performs better than initial placement and achieves comparable or better performance than cache mode of MCDRAM.
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    PublicationOpen Access
    Phase-based data placement scheme for heterogeneous memory systems
    (Institute of Electrical and Electronics Engineers (IEEE), 2018) N/A; Erten, Didem Unat; Laghari, Mohammad; Ahmad, Najeeb; Faculty Member; Graduate School of Sciences and Engineering; 219274; N/A; N/A
    Heterogeneous memory systems are equipped with two or more types of memories, which work in tandem to complement the capabilities of each other. The multiple memories can vary in latency, bandwidth and capacity characteristics across systems and they come in various configurations that can be managed by the programmer. This introduces an added programming complexity for the programmer. In this paper, we present a dynamic phase-based data placement scheme to assist the programmer in making decisions about program object allocations. We devise a cost model to assess the benefit of having an object in one type of memory over the other and apply the cost model at every application phase to capture the dynamic behaviour of an application. Our cost model takes into account the reference counts of objects and incurred transfer overhead when making a suggestion. In addition, objects can be transferred across memories asynchronously between phases to mask some of the transfer overhead. We test our cost model with a diverse set of applications from NAS Parallel and Rodinia benchmarks and perform experiments on Intel KNL, which is equipped with a high bandwidth memory (MCDRAM) and a high capacity memory (DDR). Our dynamic phase-based data placement performs better than initial placement and achieves comparable or better performance than cache mode of MCDRAM.