High performance multi-core processors are becoming an industry reality. Although multi-cores are suited for multithreaded and multi-programmed workloads, many applications are still mono-thread and multi-core performance with a single thread workload is an important issue. Furthermore, recent studies suggest that performance, power and temperature considerations of future multi-cores may necessitate activity-migration between cores.Motivated by the above, this paper investigates the performance implications of single thread migration on a multi-core. Specifically, the study considers the influence on the performance of a single thread of the following migration and multi-core parameters: frequency of migration, core warm-up modes, subset of resources that are warmed-up, number of cores, and cache hierarchy organization. The results of this study can provide insight to architects on how to design performance-efficient power and thermal strategies for a multi-core chip.The experimental results, for the benchmarks and microarchitectures used in this study, show that the performance loss due to activity migration on a multi-core with private L1s and a shared L2 can be minimized if: (a) a migrating thread continues its execution on a core that was previously visited by the thread, and (b) cores remember their predictor state since their previous activation (all other core resources can be cold). The analogous conclusions for a multi-core with private L1s and L2s and a shared L3 are: remembering the predictor state, maintaining the tags of the various L2 caches coherent and allowing L2-L2 data transfers from inactive cores to the active core.The data also show that when migration period is at least every 160K cycles, the transfer of register state between two cores and the flushing of dirty private L1 data have a negligible performance overhead.

/pdf/performance-implications-of-single-thread-migration-on-a-16vfc4xlao.pdf

Performance implications of single thread migration on a chip multi-core

Chip multiprocessors have the potential to exploit thread level parallelism, particularly in the context of embedded server farms where the available number of threads can be quite high. Unfortunately, both per-core and overall throughput are significantly impacted by the organization of the lowest level on-chip cache. On-chip caches for CMPs must be able to handle the increased demand and contention of multiple cores. To complicate the problem, cache demand changes dynamically with phases changes, context switches, power saving features, and assignments to asymmetric cores.We propose PDAS, a distributed NUCA L2 cache design with an adaptive sharing mechanism. Each core independently measures its dynamic need, and all cache resources are managed to increase utilization, reduce migrations, and lower interference. Per-core performance degradation is bounded while overall throughput is optimized, thus qualitatively improving performance of embedded systems where quality-of-service is an important characteristic.In single thread mode, PDAS, on average, improves by 26%, 27%, and 13% over Private, Shared, and NUCA caches respectively. This improvement is achieved while reducing internal migrations on average by 82% as compared to the NUCA. With thread contention, PDAS increases its performance and power advantage over prior work. The average migration reduction over NUCA increases to over 90%, and average IPC improvements over NUCA are 30%, 14%, and 35% for 2T, 3T, and 4T scenarios.

/pdf/fast-and-fair-data-stream-quality-of-service-4d97bynm25.pdf

Fast and fair: data-stream quality of service

In parallel to the changes in both the architecture domain - the move toward chip multiprocessors (CMPs) - and the application domain - the move toward increasingly data-intensive workloads - issues such as performance, energy efficiency and CPU availability are becoming increasingly critical. The CPU availability can change dynamically due to several reasons such as thermal overload, increase in transient errors, or operating system scheduling. An important question in this context is how to adapt, in a CMP, the execution of a given application to CPU availability change at runtime. Our paper studies this problem, targeting the energy-delay product (EDP) as the main metric to optimize. We first discuss that, in adapting the application execution to the varying CPU availability, one needs to consider the number of CPUs to use, the number of application threads to accommodate and the voltage/frequency levels to employ (if the CMP has this capability). We then propose to use helper threads to adapt the application execution to CPU availability change in general with the goal of minimizing the EDP. The helper thread runs parallel to the application execution threads and tries to determine the ideal number of CPUs, threads and voltage/frequency levels to employ at any given point in execution. We illustrate this idea using two applications (Fast Fourier Transform and MultiGrid) under different execution scenarios. The results collected through our experiments are very promising and indicate that significant EDP reductions are possible using helper threads. For example, we achieved up to 66.3% and 83.3% savings in EDP when adjusting all the parameters properly in applications FFT and MG, respectively.

A helper thread based EDP reduction scheme for adapting application execution in CMPs

Online transaction processing (OLTP) is at the core of many data center applications. OLTP workloads are known to have large instruction footprints that foil existing L1 instruction caches resulting in poor overall performance. Prefetching can reduce the impact of such instruction cache miss stalls, however, state-of-the-art solutions require large dedicated hardware tables on the order of 40KB in size. SLICC is a programmer transparent, low cost technique to minimize instruction cache misses when executing OLTP workloads. SLICC migrates threads, spreading their instruction footprint over several L1 caches. It exploits repetition within and across transactions, where a transaction's first iteration prefetches the instructions for subsequent iterations or similar subsequent transactions. SLICC reduces instruction misses by 58% on average for TPC-C and TPCE, thereby improving performance by 68%. When compared to a state-of-the-art prefetcher, and notwithstanding the increased storage overheads (42x as compared to SLICC), performance using SLICC is 21% higher for TPC-E and within 2% for TPC-C.

/pdf/slicc-self-assembly-of-instruction-cache-collectives-for-4sl4da6xi2.pdf

SLICC: Self-Assembly of Instruction Cache Collectives for OLTP Workloads

As we enter an era of exascale multicores, the question of efficiently supporting a shared memory model has become of paramount importance. On the one hand, programmers demand the convenience of coherent shared memory; on the other, growing core counts place higher demands on the memory subsystem and increasing on-chip distances mean that interconnect delays are becoming a significant part of memory access latencies. In this article, we first review the traditional techniques for providing a shared memory abstraction at the hardware level in multicore systems. We describe two new schemes that guarantee coherent shared memory without the complexity and overheads of a cache coherence protocol, namely execution migration and library cache coherence. We compare these approaches using an analytical model based on average memory latency, and give intuition for the strengths and weaknesses of each. Finally, we describe hybrid schemes that combine the strengths of different schemes.

/pdf/memory-coherence-in-the-age-of-multicores-1kkoau8r2t.pdf

Memory coherence in the age of multicores

We propose to modify a conventional single-chip multicore so that a sequential program can migrate from one core to another automatically during execution. The goal of execution migration is to take advantage of the overall on-chip cache capacity. We introduce the affinity algorithm, a method for distributing cache lines automatically on several caches. We show that on working-sets exhibiting a property called "splittability", it is possible to trade cache misses for migrations. Our experimental results indicate that the proposed method has a potential for improving the performance of certain sequential programs, without degrading significantly the performance of others.

/pdf/exploiting-the-cache-capacity-of-a-single-chip-multi-core-3qmc3bacob.pdf

Exploiting the cache capacity of a single-chip multi-core processor with execution migration

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

P. Michaud

Author Tools

Chat about Author

Papers

Exploiting the cache capacity of a single-chip multi-core processor with execution migration