Similarly to their work, our algorithms data allocation scheme is designed to reduce interchip communication. High performance scalable skip list for numa drops. Lads layoutaware data scheduling is an endtoend data transfer tool optimized for terabit network using a layoutaware data scheduling via pfs. To optimize performance, linux provides automated management of memory, processor, and io resources on most numa systems. Modifying the openmp program to allocate memory with affinity to each thread adds significant complexity see fig. Our runtime algorithms for numaaware task and data placement are fully automatic, applicationindependent, performanceportable across numa machines, and adapt to dynamic changes. Their paper presents an extension of their openmp runtime system that connects a thread scheduler to a numa aware memory management system, which they choose to call forestgomp. To prove our point, we focus on a primitive that is used as the.
The document is divided into categories corresponding to the type of article being referenced. Are readonly accesses to nonlocal memory somehow transparently accelerated e. Numa machines and handle different properties of graphs. Related work graph algorithms are traditionally solved over centralized and distributed graph analytics systems, which pur. Often the referenced article could have been placed in more than one category. The second option is to use existing concurrent data structures oblivious of numa called uniform memory access uma structuresincluding lockbased, lockfree, and waitfree algorithms. However, recent work on arbitration policies in the processorinterconnect 24 shows that when most but not all memory accesses are localwhich is exactly the situation for many numaaware algorithmshardware can unfairly.
All the designs and optimizations are generic, independent of the graph algorithms, and are part of our numa aware graph processing. Red hat enterprise linux numa support for hpe proliant servers. The toolbox is designed with graphical users interfaces guis and it can be readily used with little knowledge of genetic algorithms and evolutionary programming. So the question is how to make the application perform better.
The kernels support for numa systems has continued to evolve over the lifespan of the 2. The concept of a synchronizationfree fastpath previously. We also implement a readerswriter lock on top of our blocking lock. As far as i can tell the drop in performance in such algorithms is caused by nonlocal memory access from a second numa node. Numaaware datatransfer measurements for powernvlink. One io thread is sufficient for networking traffic pin io thread to device numa node let the scheduler migrate io intensive vm to device numa node high load. This paper revisits the design and implementation of distributed shared.
To reduce capacity cache misses for largevector reductions, we use strip mining for large vectors in all algorithms. We show that using numaaware task and data placement, it is possible to preserve the uniform abstraction of both computing and memory resources for taskparallel programming models while achieving high data locality. Numa nonuniform memory access is the phenomenon that memory at various points in the address space of a processor have different performance characteristics. The multicore evolution has stimulated renewed interests in scaling up applications on sharedmemory multiprocessors, significantly improving the scalability of many applications. Experimental results show that our numaaware virtual ma. Numaaware datatransfer measurements for powernvlink multi. A brief survey of numa nonuniform memory architecture. Second, inspired by vertexcuts 22 from distributed graph sys. X kernels and now includes a significant subset of the numa features expected in an enterpriseclass operating system. We introduce a novel hybrid design for memory accesses that handles the burst mode in traversal based algorithms, like bfs and sssp, and reduces the number of remote accesses and updates. Scalable and low synchronization numaaware algorithm for producerconsumer pools elad gidron cs department technion, haifa, israel. Numa oblivious data partitioning vs numa aware data partitioning. This document presents a list of articles on numa nonuniform memory architecture that the author considers particularly useful. Numa aware multicore blas matrix multiplication 3 implements mesif modi ed, exclusive, shared, invalid, forward protocol in intel nehalem a processors to maintain the data coherency 2 3.
A numaaware clustering library capable of operating. Numaaware graph mining techniques for performance and energy ef. In this situation, the reference to the article is placed in what the author thinks is the. To achieve the highest performance, we employ a combination of thread binding, numaaware thread allocation, and relaxed global coordination among threads. While allocating memory in a serial region and faulting it in a parallel region will usually impart the right affinity, the safest method is to allocate data private to. Briefly, nr implements a numaaware shared log, and then uses the log to replicate data structures consistently across numa nodes. Our new cohorting technique allows us to easily create numa aware versions of the tatasbackoff, clh, mcs, and ticket locks, to name a few. A userlevel numaaware scheduler for optimizing virtual. Evolutionary programming an overview sciencedirect topics. Numaaware concurrency control for scalable transactional memory icpp 2018, august 16, 2018, eugene, or, usa the second experiment shows the latency needed for incrementing a logically shared timestamp via a compareandswap cas primitive. Numaaware scheduling and memory allocation for data.
Lock cohorting allows one to transform any spinlock algorithm, with minimal nonintrusive changes, into a scalable numaaware spinlock. This section describes the algorithms and settings used by esxi to maximize application performance while still maintaining resource guarantees. Numa aware locks that is as simple as it is powerful. In order to achieve locality of memory access on a numa architecture, salsa chunks are kept in the. Numa aware io in virtualized systems rishi mehta, zach shen, amitabha banerjee. Accelerating bfs and sssp on a numa machine for the. Empirical memoryaccess cost models in multicore numa architectures. Pdf multicore nodes with nonuniform memory access numa are. Morseldriven query processing takes small fragments of input data morsels and schedules these to worker.
Numaaware scheduling for both memory and computebound tasks. All the designs and optimizations are generic, independent of the graph algorithms, and are part of our numaaware graph processing. The algorithm is based on a pareto ranking scheme, i. This property inspired many numaaware algorithms for operating systems. To achieve the highest performance, we employ a combination of thread binding, numa aware thread allocation, and relaxed global coordination among threads. Unlike existing numaaware solutions for data structures. The optimization is based on nonuniform memory access balanced task and loop parallelism numabtlp algorithm stirb. We evaluate our locks in both kernel space and in userspace, and find that our lock algorithms. Extending numabtlp algorithm with thread mapping based. Numaaware graph mining techniques for performance and. Nr is best suited for contended data structures, where it can outperform lockfree algorithms by 3.
The principle of keeping numa local data structures was previously used by dice et al. Why existing contention aware algorithms may hurt performance on numa systems. Numaaware scheduling and memory allocation for data flow. All the algorithms discussed in the following subsections are numaaware to reduce intersocket memory tra c. Numaaware sharedmemory collective communication for mpi. All the algorithms discussed in the following subsections are numa aware to reduce intersocket memory tra c. Extending numabtlp algorithm with thread mapping based on a. Red hat enterprise linux numa support for hpe proliant. Why existing contentionaware algorithms may hurt performance on numa systems. The linux kernel gained support for cachecoherent nonuniform memory access numa systems in the linux 2. However, to the best of our knowledge, there has been no prior effort toward constructing numaaware rw locks. Adaptive numaaware data placement and task scheduling for.
Introduction graph partitioning is used extensively to orchestrate parallel execution of graph processing in distributed systems 1, diskbased processing 2, 3 and numaaware shared memory systems 4, 5. The second option is to use existing concurrent data structures oblivious of numacalled uniform memory access uma structuresincluding lockbased, lockfree, and waitfree algorithms. First, being aware of the hierarchical parallelism and locality in numa machines, polymer is extended with a hierarchical scheduler to reduce the cost for synchronizing threads on multiple numanodes. Associating the shared data allocation with each thread in a numaaware fashion is much more complicated. The importance of such numa aware algorithm designs will only. This white paper discusses linux support for hpe proliant servers. The principle of keeping numalocal data structures was previously used by dice et al.
Numaaware mutex locks have been explored in depth 3, 7, 17, 19. This property inspired many numa aware algorithms for operating systems. As far as i can tell the drop in performance in such algorithms is caused by nonlocal memory access from a second numanode. Virtually all those locks, however, are hierarchical in their nature, thus requiring space proportional to the number of sockets. In response, we present the morseldriven query execution framework, where scheduling becomes a. Numaaware scheduling and memory allocation for dataflow. The end result is a collection of surprisingly simple numa aware algorithms that outperform the stateoftheart readerwriter locks by up to a factor of 10 in our microbenchmark experiments. Intel 64 and ia32 architectures software developers manual.
With this technique, large vectors are divided into chunks so that each chunk can t into the lastlevel cache. A case for numaaware contention management on multicore systems. The end result is a collection of surprisingly simple numaaware algorithms that outperform the stateoftheart readerwriter locks by up to a factor of 10 in our microbenchmark experiments. Similarly to their work, our algorithm s data allocation scheme is designed to reduce interchip communication. Sep 17, 2015 this document presents a list of articles on numa nonuniform memory architecture that the author considers particularly useful. In recent years, a new breed of nonuniform memory access numasystems has emerged.
But the scalability is limited within a single node. Numaaware mutex lock designs pursue only one goal reduction of the lock 158. Our rw lock algorithms build on the recently developed lock cohorting technique 7, which allows for the construction of numa aware mutual exclusion locks. Their paper presents an extension of their openmp runtime system that connects a thread scheduler to a numaaware memory management system, which they choose to call forestgomp. The algorithm gets the type of each thread in the source code based on a static analysis of the. Scalable and low synchronization numaaware algorithm. Under numa, a processor can access its own local memory faster than nonlocal memory memory local to another processor or memory shared between processors.
Existing stateoftheart contention aware algorithms work as follows on numa systems. In this paper, we propose a numaaware thread and resource scheduling for optimized data transfer in terabit network. Our runtime algorithms for numa aware task and data placement are fully automatic, applicationindependent, performanceportable across numa machines, and adapt to dynamic changes. Numaaware sharedmemory collective communication for. Moreover, these solutions are not applicable when applications compose data structures and wish to modify several of them with a single composed operation e. The importance of such numaaware algorithm designs will only.
We further add a core oversubscription policy to implement a blocking lock. The paper presents a nonuniform memory access numaaware compiler optimization for tasklevel parallel code. This encourages the design of numaaware algorithms 21, 22, 5, 23 that minimize remotenode memory accesses. For this reason, the placement of threads and memory plays a crucial role in performance. Numa aware io in virtualized systems hot interconnects. Briefly, nr implements a numa aware shared log, and then uses the log to replicate data structures consistently across numa nodes. Our new cohorting technique allows us to easily create numaaware versions of the tatasbackoff, clh, mcs, and ticket locks, to name a few. Lock cohorting allows one to transform any spinlock algorithm, with minimal nonintrusive changes, into a scalable numa aware spinlock. Design of kernel algorithms and data structures, as well as data placement selection of kernel or application io paths the linux kernels numa features evolved throughout the linux 2. Numa awareness affects all layers of the library i. Citeseerx document details isaac councill, lee giles, pradeep teregowda.
Blackbox concurrent data structures for numa architectures. Existing stateoftheart contentionaware algorithms work as follows on numa systems. A case for numaaware contention management on multicore. The importance of such numaaware algorithm designs will only increase, as future server systems are expected to feature ever larger numbers of sockets and. In recent years, a new breed of nonuniform memory access numa systems has emerged. Nonuniform memory access numa is a computer memory design used in multiprocessing, where the memory access time depends on the memory location relative to the processor. Section 7 puts it altogether and introduces graphite. Our overarching goal is to devise a methodology for developing parallel algorithms addressing these. Contents preface xiii i foundations introduction 3 1 the role of algorithms in computing 5 1.
Numa aware locks that exploit this behavior by keeping the lock ownership on the same socket, thus reducing remote cache misses and intersocket communication. Numaaware datatransfer measurements for powernvlink multigpu systems. Furthermore, our use of pagesize chunks allows for data migration in numa architectures to improve locality, as done in 8. However, it does not consider the numa nonuniform memory access architecture. It is a numaaware scheduler that implements workstealing, data distribution and more. In order to maximize processing speed, each partition should take the same. An overview numa becomes more common because memory controllers get close to execution units on microprocessors. They identify threads that are sharing a memory domain and hurting each others. Our adaptive data placement algorithm tracks the resource utilization of tasks, partitions of tables and table groups, and sockets.
Our data placement scheme guarantees that all accesses to task output data target the. Accelerating bfs and sssp on a numa machine for the graph500. The numa aware scheduling algorithm properly selects a best numa node for a vm. Userlevel scheduling on numa multicore systems under linux. Results are reported in section 8 and section 9 concludes with some remarks. Numaaware thread scheduling for big data transfers over. Numaaware multicore blas matrix multiplication 3 implements mesif modi ed, exclusive, shared, invalid, forward protocol in intel nehalem a processors to maintain the data coherency 2 3. Finally, as most graph algorithms converge asymmet rically, using a single data structure for runtime states may drasti cally degrade the performance, especially. It is a numa aware scheduler that implements workstealing, data distribution and more. This paper makes the case that data management systems need to employ designs that take into consideration the characteristics of modern numa hardware.
921 383 974 227 638 913 1011 1315 464 1484 513 769 407 1229 1019 1373 310 679 569 671 732 1230 1234 1486 1355 1363 554 613 286 1212 1494 792 1136 160 1013 240 129 1311