4,983 research outputs found
Towards a Mini-App for Smoothed Particle Hydrodynamics at Exascale
The smoothed particle hydrodynamics (SPH) technique is a purely Lagrangian
method, used in numerical simulations of fluids in astrophysics and
computational fluid dynamics, among many other fields. SPH simulations with
detailed physics represent computationally-demanding calculations. The
parallelization of SPH codes is not trivial due to the absence of a structured
grid. Additionally, the performance of the SPH codes can be, in general,
adversely impacted by several factors, such as multiple time-stepping,
long-range interactions, and/or boundary conditions. This work presents
insights into the current performance and functionalities of three SPH codes:
SPHYNX, ChaNGa, and SPH-flow. These codes are the starting point of an
interdisciplinary co-design project, SPH-EXA, for the development of an
Exascale-ready SPH mini-app. To gain such insights, a rotating square patch
test was implemented as a common test simulation for the three SPH codes and
analyzed on two modern HPC systems. Furthermore, to stress the differences with
the codes stemming from the astrophysics community (SPHYNX and ChaNGa), an
additional test case, the Evrard collapse, has also been carried out. This work
extrapolates the common basic SPH features in the three codes for the purpose
of consolidating them into a pure-SPH, Exascale-ready, optimized, mini-app.
Moreover, the outcome of this serves as direct feedback to the parent codes, to
improve their performance and overall scalability.Comment: 18 pages, 4 figures, 5 tables, 2018 IEEE International Conference on
Cluster Computing proceedings for WRAp1
MISO: Exploiting Multi-Instance GPU Capability on Multi-Tenant Systems for Machine Learning
GPU technology has been improving at an expedited pace in terms of size and
performance, empowering HPC and AI/ML researchers to advance the scientific
discovery process. However, this also leads to inefficient resource usage, as
most GPU workloads, including complicated AI/ML models, are not able to utilize
the GPU resources to their fullest extent -- encouraging support for GPU
multi-tenancy. We propose MISO, a technique to exploit the Multi-Instance GPU
(MIG) capability on the latest NVIDIA datacenter GPUs (e.g., A100, H100) to
dynamically partition GPU resources among co-located jobs. MISO's key insight
is to use the lightweight, more flexible Multi-Process Service (MPS) capability
to predict the best MIG partition allocation for different jobs, without
incurring the overhead of implementing them during exploration. Due to its
ability to utilize GPU resources more efficiently, MISO achieves 49% and 16%
lower average job completion time than the unpartitioned and optimal static GPU
partition schemes, respectively
High Performance P3M N-body code: CUBEP3M
This paper presents CUBEP3M, a publicly-available high performance
cosmological N-body code and describes many utilities and extensions that have
been added to the standard package. These include a memory-light runtime SO
halo finder, a non-Gaussian initial conditions generator, and a system of
unique particle identification. CUBEP3M is fast, its accuracy is tuneable to
optimize speed or memory, and has been run on more than 27,000 cores, achieving
within a factor of two of ideal weak scaling even at this problem size. The
code can be run in an extra-lean mode where the peak memory imprint for large
runs is as low as 37 bytes per particles, which is almost two times leaner than
other widely used N-body codes. However, load imbalances can increase this
requirement by a factor of two, such that fast configurations with all the
utilities enabled and load imbalances factored in require between 70 and 120
bytes per particles. CUBEP3M is well designed to study large scales
cosmological systems, where imbalances are not too large and adaptive
time-stepping not essential. It has already been used for a broad number of
science applications that require either large samples of non-linear
realizations or very large dark matter N-body simulations, including
cosmological reionization, halo formation, baryonic acoustic oscillations, weak
lensing or non-Gaussian statistics. We discuss the structure, the accuracy,
known systematic effects and the scaling performance of the code and its
utilities, when applicable.Comment: 20 pages, 17 figures, added halo profiles, updated to match MNRAS
accepted versio
Checkpoint restart support for heterogeneous HPC applications
As we approach the era of exa-scale computing, fault tolerance is of growing importance. The increasing number of cores as well as the increased complexity of modern heterogenous systems result in substantial decrease of the expected mean time between failures. Among the different fault tolerance techniques, checkpoint/restart is vastly adopted in supercomputing systems. Although many supercomputers in the TOP 500 list use GPUs, only a few checkpoint restart mechanism support GPUs.In this paper, we extend an application level checkpoint library, called fault tolerance interface (FTI), to support multi-node/multi-GPU checkpoints. In contrast to previous work, our library includes a memory manager, which upon a checkpoint invocation tracks the actual location of the data to be stored and handles the data accordingly. We analyze the overhead of the checkpoint/restart procedure and we present a series of optimization steps to massively decrease the checkpoint and recovery time of our implementation. To further reduce the checkpoint time we present a differential checkpoint approach which writes only the updated data to the checkpoint file. Our approach is evaluated and, in the best case scenario, the execution time of a normal checkpoint is reduced by 15x in contrast with a non-optimized version, in the case of differential checkpoint the overhead can drop to 2.6% when checkpointing every 30s.The research leading to these results has received funding from the European Union’s Horizon 2020 Programme under the LEGaTO Project (www.legato-project.eu), grant agreement #780681.Peer ReviewedPostprint (author's final draft
- …