在嵌入式系統中，草稿式記憶體經常被使用，他是一種由軟體控制資料分配的記憶體，相比於傳統快取式記憶體，草稿式記憶體具有較低的耗電與較快速的讀取速度.由於晶片面積有限，為了在不增加記憶體面積的前提下提升內存記憶體容量，有些研究利用非揮發性記憶體與靜態隨機存取記憶體組成混合性草稿記憶體，利用非揮發性記憶體的高密度優勢提升內存記憶體容量，但是由於非揮發性記憶體的寫入成本遠大於靜態隨機存取記憶體，為了減少非揮發性記憶體的寫入次數，這些研究會設計一個有效分配策略來使用靜態隨機存取記憶體與非揮發性記憶體，但是在目前的分配策略中都不考慮收集執行時資料存取行為，而是由執行前的分析，來預測資料執行時的存取行為，根據這些訊息來分配記憶體空間，然而執行前的分析，往往因為使用者對於程式執行時的輸入而做改變，執行前的分析會因此而產生改變造成錯誤的資料分配。我們決定提出一個即時管理混合性草稿式記憶體的分配策略，他是根據執行時收集記憶體寫入的操作來判斷資料的分配，由於目前在混合性草稿式記憶體並沒有即時的分配策略，我們參考由靜態隨機存取記憶體組成的草稿式記憶體即時管理方式，來設計我們的研究，而最後實驗結果我們相比同面積的混合性草稿式記憶體與靜態隨機存取記憶體組成的草稿式記憶體，並使用即時管理策略，混合性草稿式記憶體的效能將會改善37%靜態隨機存取記憶體組成的草稿式記憶體效能。

Scratch Pad Memory (SPM), a software-controlled on-chip memory, has been increasingly used in embedded system due to their higher energy and area efficiency compared to ordinary caches. In order to increase SPM capacity in same memory area, some research combine Non-Volatile Memory (NVM) with SRAM as hybrid SPM to take advantage of the high density of NVM to increase SPM capacity.. However, write operation in NVM consumes more energy than in SRAM. In order to reduce write operation in NVM, these works design allocation policy to efficient utilized Hybrid SPM but that don’t consider runtime data access behavior to allocation data. However, without considering runtime data access behavior, the above allocation policy can result in inefficient SPM utilization. For example, a data object may be regarded as a frequently-accessed object according to profiling, but may be accessed rarely during the runtime when input values change during runtime. Therefore, allocation policy considers runtime data access behavior for hybrid SPM allocation are proposed to improve the efficiency of hybrid SPM utilization. In this paper, we propose a novel online allocation policy for hybrid SPM, which uses write-read behaviors of data to determine data allocation in hybrid scratch-pad memory architecture. This policy can keep write-intensive data in SRAM and read-intensive data in NVM. The novel online hybrid SPM allocation policy can reduce energy delay product by 37% on average compared with a pure SRAM based SPM with online allocation policy.

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