Enhancement of Writeback Caching by changes in flush and its parameters

Achievement of high performance in computing or accessing of data is the aim of any system. Reduction of access time to a particular data which is present in the device is very important for the enhancement in the performance. Caching is implemented to do the same. The group of cache device and the virtual device is made as a cache group to enhance the performance of the system. The system may not be on the same condition different instances of time. There will always be a variation in io rates of the application, which is not utilized for the full extent. These differences in the io rates can be utilized effectively for the enhancement of the performance of the system. When the system is idle of with less io then the system will force the flush so that the inconsistency of data is reduced. When the system is being bombarded with io then less threads are given for the flush io. These variations in the threads assigned for the implementation of flush io will enhance the overall performance of the system

Maximum Likelihood Associative Memories

Associative memories are structures that store data in such a way that it can later be retrieved given only a part of its content -- a sort-of error/erasure-resilience property. They are used in applications ranging from caches and memory management in CPUs to database engines. In this work we study associative memories built on the maximum likelihood principle. We derive minimum residual error rates when the data stored comes from a uniform binary source. Second, we determine the minimum amount of memory required to store the same data. Finally, we bound the computational complexity for message retrieval. We then compare these bounds with two existing associative memory architectures: the celebrated Hopfield neural networks and a neural network architecture introduced more recently by Gripon and Berrou

Author retrospective for the dual data cache

In this paper we present a retrospective on our paper published in ICS 1995, which to best of our knowledge was the first paper that introduced the concept of a cache memory with multiple subcaches, each tuned for a different type of locality. In this retrospective, we summarize the main ideas of the original paper and outline some of the later work that exploited similar ideas and could have been influenced by our original paper, including two actual industrial microprocessors.Peer ReviewedPostprint (author’s final draft

Evaluating the Presence of a Victim Cache on an Arm Processor

Mobile processor is a CPU designed to save power. It is found in mobile computers and cell phones. A CPU chip, designed for portable computers, is typically housed in a smaller chip package, but more importantly, in order to run cooler, it uses lower voltages than its desktop counterpart and has more sleep mode capability. A mobile processor can be throttled down to different power levels and/or sections of the chip can be turned off entirely when not in use. ARM is a 32-bit reduced instruction set computer (RISC) instruction set architecture (ISA). The relative simplicity of ARM processors makes them suitable for low power applications. Hence ARM processors account for approximately 90% of all mobile 32-bit RISC processors. Today, mobile processors are expected to run complex, algorithm-heavy, memory-intensive applications which were originally designed and coded for general-purpose processors. Due to this we see a huge impact of the memory latencies on the execution time of applications. To reduce this impact and serve this kind of applications, the relative complexity of ARM processors has increased in the last decade by the inclusion of traditional methods like multiple issue of instructions, out-of-order instruction execution and large, associative caches. Victim Caching is another method which can be used to reduce the execution time and is currently not incorporated in the ARM processors. This method was proposed by Norman P. Jouppi in his paper “Improving Direct-Mapped Cache Performance by the Addition of a Small Fully-Associative Cache and Prefetch Buffers”. Victim Cache is defined as an extension to a direct mapped cache that adds a small, secondary, fully associative cache to store cache blocks that have been ejected from the main cache due to a capacity or conflict miss. These ejected blocks are likely to be needed again so storing them in the secondary cache should increase performance and reduce the execution times. Therefore for the Master\u27s project we re-implemented the SimpleScalar simulator for an ARM processor by incorporating the impact of Victim Cache. This re-implementation of the ARM simulator gave a significant improvement in the performance when various applications of MIBench benchmark suite were run on this simulator. It is observed to have a reduction of 1.93% in the number of clock cycles used and increase in the hit rate of Level 1cache by 2.7% over various Level 1 cache and Victim cache configurations on an average. It is also observed that the benefit of Victim cache increases as the size of Level 1 cache decreases and the performance boost obtained by the processor in presence of a Victim cache is comparable to the performance obtained when a Large, Associative Level 1 cache is used. Hence, incorporation of Victim Cache to an ARM processor is highly advantageous to the current generation of Mobile processors instead of using a Large, Associative Level 1 cache

Randomized cache placement for eliminating conflicts

Applications with regular patterns of memory access can experience high levels of cache conflict misses. In shared-memory multiprocessors conflict misses can be increased significantly by the data transpositions required for parallelization. Techniques such as blocking which are introduced within a single thread to improve locality, can result in yet more conflict misses. The tension between minimizing cache conflicts and the other transformations needed for efficient parallelization leads to complex optimization problems for parallelizing compilers. This paper shows how the introduction of a pseudorandom element into the cache index function can effectively eliminate repetitive conflict misses and produce a cache where miss ratio depends solely on working set behavior. We examine the impact of pseudorandom cache indexing on processor cycle times and present practical solutions to some of the major implementation issues for this type of cache. Our conclusions are supported by simulations of a superscalar out-of-order processor executing the SPEC95 benchmarks, as well as from cache simulations of individual loop kernels to illustrate specific effects. We present measurements of instructions committed per cycle (IPC) when comparing the performance of different cache architectures on whole-program benchmarks such as the SPEC95 suite.Peer ReviewedPostprint (published version

Eager Stack Cache Memory Transfers

The growing complexity of modern computer architectures increasingly complicates the prediction of the run-time behavior of software. For real-time systems, where a safe estimation of the program\u27s worst-case execution time is needed, time-predictable computer architectures promise to resolve this problem. The stack cache, for instance, allows the compiler to efficiently cache a program\u27s stack, while static analysis of its behavior remains easy. This work introduces an optimization of the stack cache that allows to anticipate memory transfers that might be initiated by future stack cache control instructions. These eager memory transfers thus allow to reduce the average-case latency of those control instructions, very similar to "prefetching" techniques known from conventional caches. However, the mechanism proposed here is guaranteed to have no impact on the worst-case execution time estimates computed by static analysis. Measurements on a dual-core platform using the Patmos processor and imedivision-multiplexing-based memory arbitration, show that our technique can eliminate up to 62% (7%) of the memory transfers from (respectively to) the stack cache on average over all programs of the MiBench benchmark suite

How Multithreading Addresses the Memory Wall

The memory wall is the predicted situation where improvements to processor speed will be masked by the much slower improvement in dynamic random access (DRAM) memory speed. Since the prediction was made in 1995, considerable progress has been made in addressing the memory wall. There have been advances in DRAM organization, improved approaches to memory hierarchy have been proposed, integrating DRAM onto the processor chip has been investigated and alternative approaches to organizing the instruction stream have been researched. All of these approaches contribute to reducing the predicted memory wall effect; some can potentially be combined. This paper reviews several approaches with a view to assessing the most promising option. Given the growing CPU-DRAM speed gap, any strategy which finds alternative work while waiting for DRAM is likely to be a win