Papers by mohammad albawayeh
MOHAMMAD ALBAWAYEH, 2026
This project aims to develop a smart memory management system (RAM) for modern operating systems ... more This project aims to develop a smart memory management system (RAM) for modern operating systems like Windows and Linux. By leveraging AI techniques, the system predicts application behavior, compresses inactive data, and dynamically manages background processes to reduce memory consumption by 15% to 40% without compromising overall performance.
MOHAMMAD ALBAWAYEH, 2026
Modern microprocessors employ speculative execution to maximize instruction throughput. However, ... more Modern microprocessors employ speculative execution to maximize instruction throughput. However, this optimization creates transient execution side channels, such as Spectre and Meltdown, which expose sensitive data through microarchitectural states. Current software-only mitigations incur significant performance overhead, often exceeding 30% in data-intensive workloads. This paper proposes a novel Hardware-Software Co-Design framework titled "Dynamic Context-Aware Isolation" (DCAI). DCAI introduces a specialized hardware controller that dynamically partitions cache resources and serializes speculative instructions only when processing sensitive execution contexts. Our simulation results indicate that DCAI reduces performance overhead to less than 8% while providing robust protection against known transient execution attacks.
MOHAMMAD ALBAWAYEH, 2026
Graphics Processing Units (GPUs) are pivotal in modern computational tasks, ranging from real-tim... more Graphics Processing Units (GPUs) are pivotal in modern computational tasks, ranging from real-time rendering to artificial intelligence. However, the diversity of hardware capabilities often leads to suboptimal performance on low-to mid-range systems. This paper proposes a dynamic, middleware-based adaptive framework designed to optimize GPU utilization by monitoring real-time metrics and adjusting workloads programmatically. By implementing a multi-layered optimization logic, the framework bridges the performance gap across heterogeneous hardware. Experimental results show a 35% increase in frame rate stability and a 20% reduction in thermal spikes.
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Papers by mohammad albawayeh