This paper proposes to tightly couple the thread scheduling mechanism with the cache management algorithms such that gpu cache pollution is minimized while offchip memory throughput is enhanced. Publications scs lab illinois institute of technology. In this paper, we propose a divergence aware cache dacache management that can orchestrate l1d cache management and warp scheduling together for gpgpus. In one embodiment, a continuation packet is referenced directly by a first task. Memory divergenceaware gpu cache management the 29th international conference on supercomputing ics15 january 1, 2015 eliminating intrawarp conflict misses in gpu.
Recent research, library cache coherence lcc, explored the use of timebased approaches in cmp coherence. We propose divergenceaware warp scheduling daws, which introduces a divergencebased cache footprint predictor to estimate how much l1 data cache capacity is needed to capture intrawarp locality in loops. Locality and scheduling in the massively multithreaded era. Highperformance and energyeffcient memory scheduler design. Arunkumar 4 proposed an instruction and memory divergence cache management method, based on the studying reuse behavior and spatial utilization of cache lines using program level information. Parallel architecture and system research lab pasl at auburn. View tor aamodts profile on linkedin, the worlds largest professional community.
Locality based warp scheduling in gpgpus sciencedirect. Mitigating gpu memory divergence for dataintensive. We propose the applicationaware noc aanoc management to better exploit the application. Memoryaware tlp throttling and cache bypassing for gpus. In proceedings of the ieee international symposium on performance analysis of systems and software ispass, new brunswick, nj ispass 2012 acceptance rate. Current networkonchip noc designs in gpus are agnostic to application requirements, and this leads to wasted performance in gpus multitasking. In addition, warp scheduling is very important for gpu specific cache management to reduce both intra and interwarp conflicts and maximize data locality. In this paper, we propose a divergenceaware cache dacache management that can orchestrate l1d cache management and warp scheduling together for gpgpus. The pc skip table contains one entry for each pc currently being skipped. Dacache proceedings of the 29th acm on international. Professor tor aamodt computer architecture including accelerators for deep neural networks and architecture of graphics processor units for nongraphics computing. Chulian zhang senior electrical engineer microsoft. The massive amount of memory requests generated by gpus cause cache contention and resource congestion.
Gpu enenrgy efficiency through softwarehardware codesign. Instruction and memory divergence based cache management for gpus. Localityprotected cache allocation scheme with low. View chulian zhangs profile on linkedin, the worlds largest professional community. First, we introduce a new cache indexing method that can adapt to memory accesses with different strides in this pattern, eliminate intrawarp associativity conflicts, and improves gpu cache performance. Abstractthe power consumed by memory system in gpus is a significant fraction of. Divergenceaware warp scheduling uses the information gathered from warp 0 to predict that the data loaded by warp 1s active threads will evict data reused by warp 0 which is still. Economically important server computing, big data tim rogers. In this paper, we put forward a coordinated warp scheduling and locality protected cwlp cache allocation scheme to make full use of data locality and. See the complete profile on linkedin and discover tors connections and jobs at similar companies. Divergenceaware warp scheduling ieee conference publication. We propose a divergence aware cache management technique, namely dacache, to orchestrate warp scheduling and cache management for gpgpus.
We evaluate caching effectiveness of gpu data caches for both memorycoherent and memorydivergent gpgpu benchmarks, and present the problem of partial caching in existing gpu cache management. Existing cpu cache management policies that are designed for multicore systems, can be suboptimal when directly applied to gpu caches. Gpu applications using software tools, such as autotuners 82, 89, 172, 295, 311, optimizing. On the gpu, each thread has access to shared or local memory, which is analogous to cache on the cpu. Systems, apparatuses, and methods for implementing continuation analysis tasks cats are disclosed. Ics 2002 daehyun kim, mainak chaudhuri, and mark heinrich. Improving performance of parallel io systems through selective and layoutaware ssd cache ieee transactions on parallel and distributed systems tpds, vol. The gpu scheduling mechanism swaps warps to hide memory latency. Complicate programming not always performance portable not guaranteed to improve performance sometimes impossible improve performance of programs with memory divergence. Proceedings of the 2014 international workshop on data intensive scalable computing systems, discs 14, new orleans, louisiana, usa, november 1621, 2014. Unlike prior work on cacheconscious wavefront scheduling, which makes. If one instruction fails to hit on chip, the requests are pushed to l2 cache in the memory partition through memory port and interconnect. A survey of architectural approaches for improving gpgpu.
To avoid oversubscribing the cache, divergence aware warp scheduling prevents warp 1 from entering the loop by descheduling it. Developing a resilience testbed for vulnerability analysis and hil testing of electrical grids. We propose memoryaware tlp throttling and cache bypassing matb mechanism, which can exploit data temporal locality and memory bandwidth. We demonstrate that the predictive, preemptive nature of daws can provide an additional 26% performance improvement over ccws. Cuda memory and cache architecture understanding the basic memory architecture of whatever system youre programming for is necessary to create high performance applications. Anatomy of gpu memory system for multiapplication execution. Our evaluations show that the gpu aware cache and memory management techniques proposed in this dissertation are effective at mitigating the interference caused by gpus on current and future gpu. The second mechanism, divergenceaware warp scheduling daws, introduces a divergencebased cache footprint predictor to estimate how much l1 data cache capacity is needed to capture locality in loops. Gpudmm enables dynamic memory management for discrete gpu environments by using gpu memory as a cache of cpu memory with ondemand cpugpu data transfers. Cache memory software free download cache memory top 4 download offers free software downloads for windows, mac, ios and android computers and mobile devices. Second, the massively multithreaded gpu architecture presents significant storage overheads for buffering thousands of inflight coherence requests. Our evaluations show that the gpuaware cache and memory management techniques proposed in this dissertation are effective at mitigating the interference caused by.
Threads of a given threadblock can access the onchip programmermanaged cache, termed shared memory. Highperformance and energyeffcient memory scheduler design for heterogeneous systems. Were upgrading the acm dl, and would like your input. Even though the impacts of memory divergence can be alleviated through various software techniques, architectural support for memory divergence mitigation is still highly desirable to ease the complexity in the programming and optimization of gpuaccelerated dataintensive applications. To avoid oversubscribing the cache, divergenceaware warp scheduling prevents warp 1 from entering the loop by descheduling it.
Most desktop systems consist of large amounts of system memory connected to a single cpu, which may have 2 or three levels or fully coherent cache. We propose divergenceaware warp scheduling daws, which introduces a divergencebased cache footprint predictor to estimate how much l1 data cache capacity is. Dec 07, 20 divergence aware warp scheduling uses the information gathered from warp 0 to predict that the data loaded by warp 1s active threads will evict data reused by warp 0 which is still in the loop. When gpus perform memory accesses, they usually do so through caches, just like cpus do.
In one embodiment, a system implements hardware acceleration of cats to manage the dependencies and scheduling of an application composed of multiple tasks. This paper uses hardware thread scheduling to improve the performance and energy efficiency of divergent applications on gpus. Exploring hybrid memory for gpu energy efficiency through softwarehardware codesign. Exploiting spatial locality, micro 98 a locality aware memory hierarchy for energyefficient gpu arch, micro 99 divergence aware warp scheduling, micro 100 linearly compressed pages. Leveraging cache coherence in active memory systems. Applicationaware noc management in gpus multitasking.
Bin wang software engineer arista networks linkedin. We propose a divergenceaware cache management technique, namely dacache, to orchestrate warp scheduling and cache management for gpgpus. This will cause cache thrashing and contention problems and limit gpu performance. Citeseerx document details isaac councill, lee giles, pradeep teregowda. Access patternaware cache management for improving data. In proceedings of the 2002 international conference on parallel and distributed processing techniques and applications, pages 8389, june 2002. We evaluate caching effectiveness of gpu data caches for both memory coherent and memory divergent gpgpu benchmarks, and present the problem of partial caching in existing gpu cache management. Exploiting interwarp heterogeneity to improve gpgpu. First, gpudmm simplifies the gpgpu programming by relieving the programmer of cpugpu memory management burden. Improving performance of parallel io systems through selective and layout aware ssd cache ieee transactions on parallel and distributed systems tpds, vol. This helps limit the number of accesses made to the skip pc table each cycle. A tagless cache for reducing energy, micro 97 decoupled compressed cache.
Interwarp divergence aware execution on gpus northeastern. The throughputoriented execution model in gpu introduces thousands of hardware threads, which may access the small cache simultaneously. We propose memory aware tlp throttling and cache bypassing matb mechanism, which can exploit data temporal locality and memory bandwidth. Exploiting spatial locality, micro 98 a localityaware memory hierarchy for energyefficient gpu arch, micro 99 divergenceaware warp scheduling, micro 100 linearly compressed pages. It has become an important factor affecting the performance of gpgpus. We propose a specialized cache management policy for gpgpus. Orchestrating cache management and memory scheduling for gpgpu applications by jie slides a scalable multipath microarchitecture for efficient gpu control flow by shuwen slides. Nov 27, 2017 it has become an important factor affecting the performance of gpgpus. We observe that applications can generally be classified as either networksensitive or networkinsensitive. We propose access patternaware cache management apcm, which dynamically detects the locality type of each load instruction by monitoring the accesses from one exemplary warp. The university of british columbia curriculum vitae for. Based on this discovery we argue that cache management must be done using perload locality type information, rather than applying warpwide cache management policies. In this paper, we propose a divergenceaware cache da. Tim rogers divergenceaware warp scheduling 4 motivation transfer locality management from sw to hw software solutions.
Tor aamodt is a professor in the department of electrical and computer engineering at the university of british columbia where he has been a faculty member since 2006. Power efficient sharingaware gpu data management alchem. Highperformance and energyeffcient memory scheduler. Then, we will present a divergenceaware cache management that can orchestrate l1d cache management and warp scheduling together for gpgpus. Third, these protocols increase the verification complexity of the gpu memory system. Proceedings of the international conference on supercomputing ics, pp 8998. Sung, reducing offchip memory traffic by selective cache management scheme in gpgpus, 5th annual workshop on general purpose processing with graphics processing units acm, 2012 pp. In proceedings of the 2016 ieee international symposium on workload characterization, iiswc 2016 pp.
Prior work on memory scheduling for gpus has dealt with a single application context only. This cited by count includes citations to the following articles in scholar. Gpu enenrgy efficiency through software hardware codesign. The first mechanism, cache conscious warp scheduling ccws, is an adaptive hardware mechanism that makes use of a novel locality detector to capture memory. Association for computing machinery resource library. This dissertation proposes three novel gpu microarchitecture enhancements for mitigating both the locality and utilization problems on an important class of irregular gpu applications. Even though the impacts of memory divergence can be alleviated through various software techniques, architectural support for memory divergence mitigation is still highly desirable to ease the complexity in the programming and optimization of gpu accelerated dataintensive applications. We propose divergence aware warp scheduling daws, which introduces a divergence based cache footprint predictor to estimate how much l1 data cache capacity is needed to capture intrawarp locality in loops. Localityprotected cache allocation scheme with low overhead. Extracting relevant fragments from software development video tutorials. In addition, warp scheduling is very important for gpuspecific cache management to reduce both intra and interwarp conflicts and maximize data locality. Us patent for continuation analysis tasks for gpu task.
Improve performance of programs with memory divergence. See the complete profile on linkedin and discover chulians. We propose access pattern aware cache management apcm, which dynamically detects the locality type of each load instruction by monitoring the accesses from one exemplary warp. Memory divergence or an uncoalesced memory access occurs when. Daws attempts to shift the burden of locality management from software to hardware, increasing the performance of simpler and more portable code on the gpu. The purpose was to guide scheduling decisions to improve the locality in the access stream of memory references seen by the cache. Jan 25, 2019 wang b, yu w, sun xh, wang x 2015 dacache.
Memory divergence aware gpu cache management the 29th international conference on supercomputing ics15 january 1, 2015 eliminating intrawarp conflict misses in gpu. Dimensionalityaware redundant simt instruction elimination. Divergenceaware warp scheduling ubc ece university of. In addition, warp scheduling is very important for gpuspecific cache management to reduce both intra and interwarp. Fang zhou, hai pham, jianhui yue, hao zou and weikuan yu. Cta scheduling, memory placement, cache management, and prefetching. Mitigating gpu memory divergence for dataintensive applications. It aims to make those cache blocks with good data locality stay inside l1d cache longer while maintaining onchip resources utiliza tion. Cache coherence protocol design for active memory systems. Divergenceaware warp scheduling uses the information gathered from warp 0 to predict that the data loaded by warp 1s active threads will evict data reused by warp 0 which is still in the loop. In contrast to their strong computing power, gpus have limited onchip memory space which is easy to be inadequate. In proceedings of the 29th acm on international conference on supercomputing, ics15, newport beachirvine, ca, usa, june 08 11, 2015 pp. Cuda memory and cache architecture the supercomputing blog.
1233 651 1522 1402 1196 691 562 947 1137 793 587 1435 1071 1649 636 510 1641 142 461 1288 121 133 380 834 991 535 738 53 1119 65 313 563 1472 1030