Analysis and optimization of the memory hierarchy for graph processing workloads abanti basak, shuangchen li, xing hu, sang min oh, xinfeng xie, li zhao y, xiaowei jiang y, yuan xie. Optimizations of management algorithms for multilevel. In practice, a memory system is a hierarchy of storage devices with different. Greenred productions relaxing music recommended for you. Tools for memory hierarchy optimization on preexascale. Fully associative cache memory block can be stored in any cache block writethrough cache write store changes both cache and main memory. With this optimization, the cache doesnt stop for a miss, but continues to. Lecture 8 memory hierarchy philadelphia university. A large body of previous work has also considered data locality optimization, but focuses exclusively on cpu and data caches optimization 8,30,39. Analysis and optimization of the memory hierarchy for.
Program optimizations for the cpu memory hierarchy usually assume that a. Data memory hierarchy optimization and partitioning for a widely used multimedia application kernel known as the hierarchical motion estimation algorithm is undertaken, with the use of global loop. Next lecture 18 locality cachefriendly code optimization memory hierarchy caching. The memory hierarchy was developed based on a program behavior known as locality of references. Analysis and optimization of the memory hierarchy for graph processing workloads abstract. Memory hierarchiesbasic design and optimization techniques submitted by rahul sawant, bharath h. We identify the memory hierarchy as an important opportunity for performance optimization, and present new insights pertaining to how search stresses the cache hierarchy, both for instructions and data. Processor speed is increasing at a very fast rate comparing to the access latency of the main memory. A hardwarebased unified memory hierarchy for systems. The diagram below shows a highlevel design for the back end of an optimizing compiler, so you can see where register allocation fits in. It is assumed that the frequency of usage of the information is known a priori.
The effect of this gap can be reduced by using cache memory in an efficient manner. In addition, the search space is dicult to model analytically since performance can. The design goal is to achieve an effective memory access time t10. The figure below clearly demonstrates the different levels of memory hierarchy.
Advanced register allocation optional memory caches. Study on memory hierarchy optimizations sreya sreedharan,shimmi asokan. Fully associative, direct mapped, set associative 2. You have to revisit amdahls law every time you applied some optimization. The memory hierarchy design in a computer system mainly includes different storage devices. Data placement optimization in gpu memory hierarchy using predictive modeling larisa stoltzfus, murali emani, peihung lin, chunhua liao university of edinburgh uk, lawrence livermore national laboratory mchpc18. Memory hierarchy performance two indirect performance measures have waylaid many a computer designer. A memory hierarchy in computer storage distinguishes each level in the hierarchy by.
However, many details of the gpu memory hierarchy are not released by gpu vendors. Data memory hierarchy optimization and partitioning for a widely used multimedia application kernel known as the hierarchical motion estimation algorithm is undertaken, with the use of global loop and datareuse transformations for three different. We show that, contrary to conventional wisdom, there is signi. Memory hierarchiesbasic design and optimization techniques. Bitwidth constrained memory hierarchy optimization for realtime video systems. Further, program generators are discussed as a way to reduce the implementation and optimization effort. Softwarecontrolled prefetching requires support from both hardware and software. Combining models and guided empirical search to optimize.
To address the need to improve memory placement for applications as described above, a performance analysis toolkit augmenting an existing overall performance tools framework is needed, that can be utilized by developers to guide code modernization and optimization on. Survey on memory hierarchies basic design and cache. The ability to explicitly represent relationships between entities gives graph analytics a significant performance advantage over traditional relational databases. The following memory hierarchy diagram is a hierarchical pyramid for computer memory. Nonvolatile memory allocation and hierarchy optimization for highlevel synthesis shuangchen li. Two running examples are used to demonstrate these techniques. Pdf bitwidth constrained memory hierarchy optimization. The performance of irregular applications on modern computer systems is hurt by the wide gap between cpu and memory speeds because these applications typically underutilize multilevel memory hierarchies, which help hide this gap. Memory hierarchy 2 cache optimizations cmsc 411 some from patterson, sussman, others 2 so far. Memory hierarchy optimizations stanford university. Most of the computers were inbuilt with extra storage to run more powerfully beyond the main memory capacity.
Fully associative cache memory block can be stored in any cache block writethrough cache write store changes both cache and main memory right away reads only require getting block on cache miss. Analysis and optimization of the memory hierarchy for graph processing workloads abanti basak, shuangchen li, xing hu, sang min oh, xinfeng xie, li zhaoy, xiaowei jiangy, yuan xie university of california, santa barbara alibaba, inc. Sequential read tput 550 mbs sequential write tput 470 mbs. Survey on memory hierarchies basic design and cache optimization techniques abstract in this paper we provide a comprehensive survey of the past and current work of memory hierarchies and optimizations with a focus on cache optimizations. Cs 267 applications of parallel computers lecture 2. In the computer system design, memory hierarchy is an enhancement to organize the memory such that it can minimize the access time. Specifically, this shows how the backend translates the ast. In fact, this equation can be implemented in a very simple way if the number of blocks in the cache is a power of two, 2x, since block address in main memory mod 2x x lowerorder bits of the block address, because the remainder of dividing by 2x in binary representation is given by the x lowerorder bits. Outline fermikepler architecture kernel optimizations launch configuration global memory throughput. An uncommon case will hopefully become the new common case. Locality cachefriendly code optimization memory hierarchy caching cache memories. Nonvolatile memory allocation and hierarchy optimization. Memory hierarchy five ways to reduce miss penalty second level cache professor randy h. A read is counted each time someone views a publication summary such as the title, abstract, and list of authors, clicks on a figure, or views or downloads the fulltext.
Due to the ever increasing performance gap between the processor and the main memory, it becomes crucial to bridge the gap by designing an efficient memory. Workshop on memory centric high performance computing. Ramaprasad sushrut govindwar, neelima mothe computer and information science department. Memory music, improve memory and concentration, binaural beats focus music duration. Graph processing is an important analysis technique for a wide range of big data applications. Data cache optimization can be further classified on to data access optimization and data layout optimization. Logical cache line corresponds to n physical lines.
Fraction of memory references not found in cache missesreferences typical numbers. Data access optimization is restructuring the code by changing the order of execution of the program. Name and a sentence on expertise for each member problem description what is the computation and why is it important. As a programmer, you need to understand marruecos lonely planet espaol pdf the memory hierarchy because it. One performance optimization that can be paired with all of the other algorithms is the use of cuda hostmapped memory. In order to reach the conclusion that our hypothesis is correct, we investigated various paging algorithms, and found the ones that could be adapted successfully from twolevel memory hierarchy to. The optimization of memory hierarchy involves the selection of types and sizes of memory devices such that the average access time to an information block is a minimum for a particular cost constraint. Memory hierarchies and optimizing matrix multiplication.
Polyhedralbased data reuse optimization for configurable. Hostmapped memory allocations are areas of host memory that are made directly accessible to the gpu through ondemand transparent initiation of pciexpress transfers between the host and gpu. Optimization of memory hierarchies in multiprogrammed. Various hardware and software approaches to improve the memory performance have been proposed recently. Extensive experiments, on a benchmark set of 44 matrices and 4 platforms, show that speedups of. Since average memory access delay is an additive component of the overall cmp cpi 3, our optimization results can be incorporated into a larger cores vs. Data placement optimization in gpu memory hierarchy using. In this article, we describe how to ease memory management between a central processing unit cpu and one or multiple discrete graphic processing units gpus by architecting a novel hardwarebased unified memory hierarchy umh. Cuda memory optimizations for large datastructures in the. A promising technique to mitigate the impact of long cache miss penalties is softwarecontrolled prefetching. Correct unit in which to count memory accesses directmapped. Common theme in the memory hierarchy random writes are somewhat slower erasing a block takes a long time 1 ms modifying a block page requires all other pages to be copied to new block in earlier ssds, the readwrite gap was much larger. The designing of the memory hierarchy is divided into two. Principle at any given time, data is copied between only two adjacent levels.
This paper investigates using data and computation reorderings to improve memory hierarchy utilization for irregular applications. Firstly we discuss various types of memory hierarchies and basic optimizations possible. Loop transformations for data locality optimization are only an enabler for effective onchip data reuse. This requires structuring algorithms and placing data so that data references are serviced by levels of the memory hierarchy as close to the processors as possible. Performance optimization an overview sciencedirect topics. Second, the gpu runs programs in a simt2 manner where each instruction stream is a thread, so that the optimization for gpu memory hierarchy must be tuned for the collection of memory access streams from multiple threads. Optimizing for the memory hierarchy topics impact of caches on performance memory hierarchy considerations systems i. Abstract cache is an important factor that affects total system performance of computer architecture.
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