![]() ![]() That means that reading or writing a character, short, or int from the pointer position will not result in changing the pointer position. ![]() Initially all pointers are by default static. The developer can set the pointer offset from the start of the pad, and control the mode of the pointer. Each pointer starts out pointing at the beginning of the Scratchpad, index 0. Pointers act like an open file handle into the BrainStem scratchpad. The host application interacts with the Scratchpad via a BrainStem entity called a Pointer. if you read out multi-byte value as a series of bytes, keep this in mind. Note: The BrainStem module stores values in little-endian format. The developer can then access this value as an integer in a reflex routine. Be aware that pad declarations can overlap indices, which may cause issues if it is not an intended overlap. The figure below shows the relationship of the byte array nature of the scratchpad to the overlay of structure that the named pad variables provide. This declaration reserves the first 4 bytes of the pad as an integer literal with the name timing. The pad declaration syntax looks something like this On most brainstem modules, the scratchpad is 300 bytes long. the Reflex pad access syntax allows the developer to overlay simple structures over the contents of the pad and access components as named characters, shorts and integers. The scratchpad is a memory byte buffer, with no inherent structure. ![]() The scratchpad is a volatile memory store, and is not preserved across a reboot or reset of the Brainstem module.įrom the reflex side the scratchpad is accessed through a declaration style syntax. The Scratchpad is accessed from the host and from the BrainStem module in two separate ways, this can be slightly more complex to work with at first, but leads to a couple of powerfull access patterns for reflex/host applications. It serves as a simple interprocess communication channel for separate Reflex routines, as well as a communication channel between the host and reflex code running on the BrainStem module. Youngbin Kim, Jian Cai, Yooseong Kim, Kyoungwoo Lee, Aviral Shrivastava, “Splitting functions in code management on scratchpad memories”, International Conference On Computer Aided Design (ICCAD), Nov, 2016.The BrainStem scratchpad is a shared memory on a brainstem module which is accessible from both the host and Reflex code.Jian Cai, Yooseong Kim, Youngbin Kim, Aviral Shrivastava, Kyoungwoo Lee, “Reducing code management overhead in software-managed multicores”, Design, Automation & Test in Europe Conference & Exhibition (DATE), Mar, 2017.The evaluation shows that our optimization technique improves performance by 16% on average, which can only be achieved by using 20% more SPM space if without function-splitting. In this work, we proposed a function splitting technique that mitigate these fundamental limitations. Therefore, their performance is limited by the existing calling relationships between functions and the code size of the functions. Although there have been many studies to find a good mapping from the given program and SPM size, they keep the call graph and functions of the program unchanged. In this scheme, SPM is divided multiple regions and functions of a program are mapped to the one of the regions. Overlay-based technique is a popular method to mange the code using a SPM. Data transfer between main memory and the SPM should be managed either by programmer or compiler, typically via the direct memory access (DMA) instructions. On the other hand, the benefit comes at the cost of explicit management of data. It has been studied as a scalable and energy-efficient alternative to the caches since it has simple design and does not increase the unnecessary traffic in the bus as the core scales. Scratchpad Memory (SPM) is a software-managed SRAM memory, which does not have hardware logics to automatically capture the locality (e.g. While cache has been adopted widely to accelerate the memory accesses transparently, it is getting more difficult to maintain cache-based architecture in the many-core systems, mainly due to the cache coherency traffic. As the number of core increases, scalability is becoming an important criteria in computer architecture design. ![]()
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