NUMASK: High Performance Scalable Skip List for NUMA

This paper presents NUMASK, a skip list data structure specifically designed to exploit the characteristics of Non-Uniform Memory Access (NUMA) architectures to improve performance. NUMASK deploys an architecture around a concurrent skip list so that all metadata accesses (e.g., traversals of the skip list index levels) read and write memory blocks allocated in the NUMA zone where the thread is executing. To the best of our knowledge, NUMASK is the first NUMA-aware skip list design that goes beyond merely limiting the performance penalties introduced by NUMA, and leverages the NUMA architecture to outperform state-of-the-art concurrent high-performance implementations. We tested NUMASK on a four-socket server. Its performance scales for both read-intensive and write-intensive workloads (tested up to 160 threads). In write-intensive workload, NUMASK shows speedups over competitors in the range of 2x to 16x

Lock cohorting: A general technique for designing NUMA locks

Multicore machines are quickly shifting to NUMA and CC-NUMA architectures, making scalable NUMA-aware locking algorithms, ones that take into account the machines' non-uniform memory and caching hierarchy, ever more important. This paper presents lock cohorting, a general new technique for designing NUMA-aware locks that is as simple as it is powerful. Lock cohorting allows one to transform any spin-lock algorithm, with minimal non-intrusive changes, into scalable NUMA-aware spin-locks. Our new cohorting technique allows us to easily create NUMA-aware versions of the TATAS-Backoff, CLH, MCS, and ticket locks, to name a few. Moreover, it allows us to derive a CLH-based cohort abortable lock, the first NUMA-aware queue lock to support abortability. We empirically compared the performance of cohort locks with prior NUMA-aware and classic NUMA-oblivious locks on a synthetic micro-benchmark, a real world key-value store application memcached, as well as the libc memory allocator. Our results demonstrate that cohort locks perform as well or better than known locks when the load is low and significantly out-perform them as the load increases

Advanced synchronization techniques for task-based runtime systems

Task-based programming models like OmpSs-2 and OpenMP provide a flexible data-flow execution model to exploit dynamic, irregular and nested parallelism. Providing an efficient implementation that scales well with small granularity tasks remains a challenge, and bottlenecks can manifest in several runtime components. In this paper, we analyze the limiting factors in the scalability of a task-based runtime system and propose individual solutions for each of the challenges, including a wait-free dependency system and a novel scalable scheduler design based on delegation. We evaluate how the optimizations impact the overall performance of the runtime, both individually and in combination. We also compare the resulting runtime against state of the art OpenMP implementations, showing equivalent or better performance, especially for fine-grained tasks.This project is supported by the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No.s 754304 (DEEP-EST), by the Spanish Ministry of Science and Innovation (contract PID2019-107255GB and TIN2015-65316P) and by the Generalitat de Catalunya (2017-SGR-1414).Peer ReviewedPostprint (author's final draft

Invasive compute balancing for applications with shared and hybrid parallelization

This is the author manuscript. The final version is available from the publisher via the DOI in this record.Achieving high scalability with dynamically adaptive algorithms in high-performance computing (HPC) is a non-trivial task. The invasive paradigm using compute migration represents an efficient alternative to classical data migration approaches for such algorithms in HPC. We present a core-distribution scheduler which realizes the migration of computational power by distributing the cores depending on the requirements specified by one or more parallel program instances. We validate our approach with different benchmark suites for simulations with artificial workload as well as applications based on dynamically adaptive shallow water simulations, and investigate concurrently executed adaptivity parameter studies on realistic Tsunami simulations. The invasive approach results in significantly faster overall execution times and higher hardware utilization than alternative approaches. A dynamic resource management is therefore mandatory for a more efficient execution of scenarios similar to our simulations, e.g. several Tsunami simulations in urgent computing, to overcome strong scalability challenges in the area of HPC. The optimizations obtained by invasive migration of cores can be generalized to similar classes of algorithms with dynamic resource requirements.This work was supported by the German Research Foundation (DFG) as part of the Transregional Collaborative Research Centre ”Invasive Computing” (SFB/TR 89)

Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS

GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world. Here, we describe some of the ways we have been able to realize this through the use of parallelization on all levels, combined with a constant focus on absolute performance. Release 4.6 of GROMACS uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration, and both OpenMP and MPI parallelism within and between nodes, respectively. The recent work on acceleration made it necessary to revisit the fundamental algorithms of molecular simulation, including the concept of neighborsearching, and we discuss the present and future challenges we see for exascale simulation - in particular a very fine-grained task parallelism. We also discuss the software management, code peer review and continuous integration testing required for a project of this complexity.Comment: EASC 2014 conference proceedin