Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 139 for “"Memory systems"”.
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Page management in hybrid memory systems
Recent byte-addressable Non-Volatile Memory (NVM) technologies enable hybrid memory systems comprising of both DRAM and NVM technologies. Such systems have the potential to address the capacity requirements of data intensive workloads and achieve high performance. The main challenge lies in …
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Intelligent cache management for heterogeneous memory systems
… important for enabling effective heterogeneous memory systems that can transparently provide the bandwidth of high-bandwidth memories and the capacity of high-capacity memories. This dissertation investigates enabling intelligent cache management for tag-inside-cacheline DRAM cache designs. Such …
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Specialization without complexity in heterogeneous memory systems
… an important challenge. Early heterogeneous systems were loosely coupled and lacked a shared coherent memory interface, so specialization was reserved for highly regular code patterns with coarse-grained synchronization requirements. More recently, the need to accelerate applications with …
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Characterization and Exploitation of GPU Memory Systems
… of threads that can be run concurrently on these systems allow applications which have data-parallel computations to achieve better performance when compared to traditional CPU systems. However, the GPU is not perfect for all types of computation. The massively parallel SIMT architecture of the …
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Tunable shared-memory abstractions for distributed-memory systems
Distributed memory multiprocessor architectures offer enormous computational power, by exploiting the concurrent execution of many loosely connected processors. Yet, such scalability is not without price. Interface delays and low interconnection bandwidth to the distributed memories make internode …
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Evaluating transformers as memory systems in reinforcement learning
Memory is an important component of effective learning systems and is crucial in non-Markovian as well as partially observable environments. In recent years, Long Short-Term Memory (LSTM) networks have been the dominant mechanism for providing memory in reinforcement learning, however, the success …
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Dynamic computation migration in distributed shared memory systems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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Automatic data aggregation for software distributed shared memory systems
Software Distributed Shared Memory (DSM) provides a shared-memory abstraction on distributed memory hardware, making a parallel programmer's task easier. Unfortunately, software DSM is less efficient than the direct use of the underlying message-passing hardware. The chief reason for this is that …
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Performance Evaluation of Memory Systems for High-Speed Computers
High speed computer systems pose two significant problems for memory system designers. How to design memory systems to meet the memory access performance required by the processors and how to evaluate proposed memory designs. This thesis addresses these two issues.
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Transient Error Recovery Techniques for Pipelines and Memory Systems
… errors. Scrubbing methods are suggested for memory systems and retry techniques are discussed for pipelines. A probabilistic model for the activity of faulty periods is introduced, and a fault analysis is carried out to decide the optimum length of the retry period, T. Distribution functions …
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Performance portability of parallel kernels on shared-memory systems
This work describes my solution to the performance portability problem: between CPUs and GPUs in particular, but laying the foundation for even broader performance portability support. I argue that the best approach is to use a language like OpenCL as a portable, low-level programming model with …
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Code generation of array constructs for distributed memory systems
Programming for high-performance systems to fully utilize the potential of the computing system is a complex problem. This is particularly evident when programming distributed memory clusters containing multiple NUMA chips and GPUs on each node since it would require a complex combination of MPI, …
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Architectural support to exploit commutativity in shared-memory systems
Parallel systems are limited by the high costs of communication and synchronization. Exploiting commutativity has historically been a fruitful avenue to reduce traffic and serialization. This is because commutative operations produce the same final result regardless of the order they are performed …
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Application of the Plasma Display Technique to Associative Memory Systems
Made available in DSpace on 2014-12-10T19:07:05Z (GMT). No. of bitstreams: 1 7310056.pdf: 3447789 bytes, checksum: 54bf9fbd96a5a168d81e73da3bd4df95 (MD5) Previous issue date: 1972
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Memory access patterns and page promotion in hybrid memory systems
Hybrid heterogeneous memory systems are becoming increasingly popular as traditional memory systems are hitting performance and energy walls in processing data-intensive applications, which are becoming the norm with the resurgence of machine learning, big data, graph analytics, and database …
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Emulation of microprocessor memory systems using the RAMP design framework
… and the academic world focused on multiprocessor systems, the RAMP project is aiming to provide the infrastructure for supporting high-speed emulation of large scale, massively-parallel multiprocessor systems using FPGAs. The RAMP design framework provides the platform for building this …
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The GraphGrind Framework: Fast Graph Analytics on Large Shared-Memory Systems
As shared memory systems support terabyte-sized main memory, they provide an opportunity to perform efficient graph analytics on a single machine. Graph analytics is characterised by frequent synchronisation, which is addressed in part by shared memory systems. However, performance is limited by …
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Learning and memory systems supporting decision making in the human brain
… learned. In the brain, two prominent learning systems have been identified and each is likely to guide decisions in different ways. Research on decision making has primarily focused on a reward learning system in the striatum. These studies have illuminated the how repeated choices and rewards …
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Estradiol Has Distinct Effects on the Hippocampal and Striatal Memory Systems
Findings from these studies highlight the distinct actions of estradiol in the hippocampus to enhance place learning and in the striatum to impair response learning. By altering the responsiveness of hippocampal and striatal cells to experience, estradiol biases the type of information obtained, …
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