Compiler driven data layout optimization for regular/irregular array access patterns

Cho, Doosan,Pasricha, Sudeep,Issenin, Ilya,Dutt, Nikil,Paek, Yunheung,Ko, SunJun Association for Computing Machinery 2008 ACM SIGPLAN Notices Vol.43 No.7

A Case Study of a Navigator Optimization Process

Cho, Doosan The Institute of Internet 2017 Journal of Advanced Smart Convergence Vol.6 No.1

When mobile navigator device accesses data randomly, the cache memory performance is rapidly deteriorated due to low memory access locality. For instance, GPS (General Positioning System) of navigator program for automobiles or drones, that are currently in common use, uses data from 32 satellites and computes current position of a receiver. This computation of positioning is the major part of GPS which accounts more than 50% computation in the program. In this computation task, the satellite signals are received in real time and stored in buffer memories. At this task, since necessary data cannot be sequentially stored, the data is read and used at random. This data accessing patterns are generated randomly, thus, memory system performance is worse by low data locality. As a result, it is difficult to process data in real time due to low data localization. Improving the low memory access locality inherited on the algorithms of conventional communication applications requires a certain optimization technique to solve this problem. In this study, we try to do optimizations with data and memory to improve the locality problem. In experiment, we show that our case study can improve processing speed of core computation and improve our overall system performance by 14%.

A Study on Efficient Use of Dual Data Memory Banks in Flight Control Computers

Cho, Doosan The Institute of Internet 2017 International Journal of Internet, Broadcasting an Vol.9 No.1

Over the past several decades, embedded system and flight control computer technologies have been evolved to meet the diverse needs of the mobile device market. Current embedded systems are at the heart of technologies that can take advantage of small-sized specialized hardware while still providing high-efficiency performance at low cost. One of these key technologies is multiple memory banks. For example, a dual memory bank can provide two times more memory bandwidth in the same memory space. This benefit take lower cost to provide the same bandwidth. However, there is still few software technologies to support the efficient use of multiple memory banks. In this study, we present a technique to efficiently exploit multiple memory banks by software support. Specifically, our technique use an interference graph to optimally allocate data to different memory banks by an optimizing compiler. As a result, the execution time can be improved upto 7% with the proposed technique.

Adaptive Scratch Pad Memory Management for Dynamic Behavior of Multimedia Applications

Doosan Cho,Pasricha, S.,Issenin, I.,Dutt, N.D.,Minwook Ahn,Yunheung Paek IEEE 2009 IEEE transactions on computer-aided design of inte Vol.28 No.4

<P>Exploiting runtime memory access traces can be a complementary approach to compiler optimizations for the energy reduction in memory hierarchy. This is particularly important for emerging multimedia applications since they usually have input-sensitive runtime behavior which results in dynamic and/or irregular memory access patterns. These types of applications are normally hard to optimize by static compiler optimizations. The reason is that their behavior stays unknown until runtime and may even change during computation. To tackle this problem, we propose an integrated approach of software [compiler and operating system (OS)] and hardware (data access record table) techniques to exploit data reusability of multimedia applications in Multiprocessor Systems on Chip. Guided by compiler analysis for generating scratch pad data layouts and hardware components for tracking dynamic memory accesses, the scratch pad data layout adapts to an input data pattern with the help of a runtime scratch pad memory manager incorporated in the OS. The runtime data placement strategy presented in this paper provides efficient scratch pad utilization for the dynamic applications. The goal is to minimize the amount of accesses to the main memory over the entire runtime of the system, which leads to a reduction in the energy consumption of the system. Our experimental results show that our approach is able to significantly improve the energy consumption of multimedia applications with dynamic memory access behavior over an existing compiler technique and an alternative hardware technique.</P>

A Study on Effect of Code Distribution and Data Replication for Multicore Computing Architectures

Doosan Cho 국제문화기술진흥원 2021 International Journal of Advanced Culture Technolo Vol.9 No.4

A multicore system must be able to take full advantage of the program's instruction and data parallelism. This study introduces the data replication technique as a support technique to maximize the program's instruction and data parallelism. Instruction level parallelism can be limited by data dependency. In this case, if data is replicated to each processor core and used, instruction level parallelism can be used to the maximum. The technique proposed in this study can maximize the performance improvement effect when applied to scientific applications such as matrix multiplication operation.

A Technique for Improving the Performance of Cache Memories

Cho, Doosan The Institute of Internet 2021 International Journal of Internet, Broadcasting an Vol.13 No.3

In order to improve performance in IoT, edge computing system, a memory is usually configured in a hierarchical structure. Based on the distance from CPU, the access speed slows down in the order of registers, cache memory, main memory, and storage. Similar to the change in performance, energy consumption also increases as the distance from the CPU increases. Therefore, it is important to develop a technique that places frequently used data to the upper memory as much as possible to improve performance and energy consumption. However, the technique should solve the problem of cache performance degradation caused by lack of spatial locality that occurs when the data access stride is large. This study proposes a technique to selectively place data with large data access stride to a software-controlled cache. By using the proposed technique, data spatial locality can be improved by reducing the data access interval, and consequently, the cache performance can be improved.

Efficient Use of On-chip Memory through Profile-Driven Array Reorganization

Cho, Doosan,Youn, Jonghee Institute of Embedded Engineering of Korea 2011 대한임베디드공학회논문지 Vol.6 No.6

In high performance embedded systems, the use of multiple on-chip memories is an essential architectural feature for exploiting inherent parallelism in multimedia applications. This feature allows multiple data accesses to be executed in parallel. However, it remains difficult to effectively exploit of multiple on-chip memories. The successful use of this architecture strongly depends on how to efficiently detect and exploit memory parallelism in target applications. In this paper, we propose a technique based on a linear array access descriptor [1], which is generated from profiled data, to detect and exploit memory parallelism. The proposed technique tackles an array reorganization problem to maximize memory parallelism in multimedia applications. We present preliminary experiments applying the proposed technique onto a representative coarse grained reconfigurable array processor (CGRA) with multimedia kernel codes. Our experimental results demonstrate that our technique optimizes data placement by putting independent data on separate storage. The results exhibit 9.8% higher performance on average compared to the existing method.

A Study on Efficient Use of Dual Data Memory Banks in Flight Control Computers

Doosan Cho 한국인터넷방송통신학회 2017 International Journal of Internet, Broadcasting an Vol.9 No.1

Over the past several decades, embedded system and flight control computer technologies have been evolved to meet the diverse needs of the mobile device market. Current embedded systems are at the heart of technologies that can take advantage of small-sized specialized hardware while still providing high-efficiency performance at low cost. One of these key technologies is multiple memory banks. For example, a dual memory bank can provide two times more memory bandwidth in the same memory space. This benefit take lower cost to provide the same bandwidth. However, there is still few software technologies to support the efficient use of multiple memory banks. In this study, we present a technique to efficiently exploit multiple memory banks by software support. Specifically, our technique use an interference graph to optimally allocate data to different memory banks by an optimizing compiler. As a result, the execution time can be improved upto 7% with the proposed technique.

A Case Study of a Navigator Optimization Process

Doosan Cho 한국인터넷방송통신학회 2017 Journal of Advanced Smart Convergence Vol.6 No.1

When mobile navigator device accesses data randomly, the cache memory performance is rapidly deteriorated due to low memory access locality. For instance, GPS (General Positioning System) of navigator program for automobiles or drones, that are currently in common use, uses data from 32 satellites and computes current position of a receiver. This computation of positioning is the major part of GPS which accounts more than 50% computation in the program. In this computation task, the satellite signals are received in real time and stored in buffer memories. At this task, since necessary data cannot be sequentially stored, the data is read and used at random. This data accessing patterns are generated randomly, thus, memory system performance is worse by low data locality. As a result, it is difficult to process data in real time due to low data localization. Improving the low memory access locality inherited on the algorithms of conventional communication applications requires a certain optimization technique to solve this problem. In this study, we try to do optimizations with data and memory to improve the locality problem. In experiment, we show that our case study can improve processing speed of core computation and improve our overall system performance by 14%.

Memory Design for Artificial Intelligence

Doosan Cho 한국인터넷방송통신학회 2020 International Journal of Internet, Broadcasting an Vol.12 No.1

Artificial intelligence (AI) is software that learns large amounts of data and provides the desired results for certain patterns. In other words, learning a large amount of data is very important, and the role of memory in terms of computing systems is important. Massive data means wider bandwidth, and the design of the memory system that can provide it becomes even more important. Providing wide bandwidth in AI systems is also related to power consumption. AlphaGo, for example, consumes 170 kW of power using 1202 CPUs and 176 GPUs. Since more than 50% of the consumption of memory is usually used by system chips, a lot of investment is being made in memory technology for AI chips. MRAM, PRAM, ReRAM and Hybrid RAM are mainly studied. This study presents various memory technologies that are being studied in artificial intelligence chip design. Especially,MRAM and PRAM are commerciallized for the next generation memory. They have two significant advantages that are ultra low power consumption and nearly zero leakage power. This paper describes a comparative analysis of the four representative new memory technologies.