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 6 of 6 for “"Processing In Memory"”.
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Reliable processing-in-memory
Processing-in-memory (PIM) architectures integrate compute units within memory, enhancing performance and efficiency but introducing significant reliability challenges. These challenges arise from the inherent conflict between localized data accesses, which minimize data movement, and the necessity …
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Energy-aware DNN Quantization for Processing-In-Memory Architecture
With increasing computational cost of deep neural network (DNN), many efforts to develop energy-efficient intelligent system have been proposed from dedicated hardware platforms to model compression algorithms. Recently, hardware-aware quantization algorithms have shown further improvement in the …
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Secure Circuits: Efficient hardware countermeasures against physical side-channel attacks
The adoption of Artificial Intelligence (AI) and IoT devices has seen unprecedented growth in recent times. AI engines demand more processing capabilities while simultaneously handling sensitive user information and proprietary IP. Concurrently, IoT devices generate vast amounts of sensitive data, …
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Efficient, Accurate, and Flexible PIM Inference through Adaptable Low-Resolution Arithmetic
Processing-In-Memory (PIM) accelerators have the potential to efficiently run Deep Neural Network (DNN) inference by reducing costly data movement and by using resistive RAM (ReRAM) for efficient analog compute. Unfortunately, overall PIM accelerator efficiency and throughput are limited by …
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Highly Efficient Neuromorphic Computing Systems With Emerging Nonvolatile Memories
<p>Emerging nonvolatile memory based hardware neuromorphic computing systems have enabled the implementation of general vector-matrix multiplication in a manner to fuse computation and memory at the same physical location. However, there remain three major challenges in designing such neuromorphic …
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Domain-specific accelerators using optically-addressed phase change memory
In recent years, the exponential growth in data generation and the increasing complexity of computational tasks have created a pressing need for more efficient computing solutions. To address this demand, researchers have developed domain-specific accelerators (DSAs) for various applications, …