TY - GEN
AB - In scientific computing, the acceleration of atomistic computer simulations
by means of custom hardware is finding ever growing application. A major
limitation, however, is that the high efficiency in terms of performance and
low power consumption entails the massive usage of low-precision computing
units. Here, based on the approximate computing paradigm, we present an
algorithmic method to rigorously compensate for numerical inaccuracies due to
low-accuracy arithmetic operations, yet still obtaining exact expectation
values using a properly modified Langevin-type equation.
AU - Rengaraj, Varadarajan
AU - Lass, Michael
AU - Plessl, Christian
AU - Kühne, Thomas
ID - 12878
T2 - arXiv:1907.08497
TI - Accurate Sampling with Noisy Forces from Approximate Computing
ER -
TY - CONF
AU - Gorlani, Paolo
AU - Kenter, Tobias
AU - Plessl, Christian
ID - 15478
T2 - Proceedings of the International Conference on Field-Programmable Technology (FPT)
TI - OpenCL Implementation of Cannon's Matrix Multiplication Algorithm on Intel Stratix 10 FPGAs
ER -
TY - CONF
AB - This paper describes a data structure and a heuristic to plan and map arbitrary resources in complex combinations while applying time dependent constraints. The approach is used in the planning based workload manager OpenCCS at the Paderborn Center for Parallel Computing (PC\(^2\)) to operate heterogeneous clusters with up to 10000 cores. We also show performance results derived from four years of operation.
AU - Keller, Axel
ED - Klusáček, D.
ED - Cirne, W.
ED - Desai, N.
ID - 22
KW - Scheduling Planning Mapping Workload management
SN - 978-3-319-77398-8
T2 - Proc. Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP)
TI - A Data Structure for Planning Based Workload Management of Heterogeneous HPC Systems
VL - 10773
ER -
TY - CONF
AB - We present the submatrix method, a highly parallelizable method for the approximate calculation of inverse p-th roots of large sparse symmetric matrices which are required in different scientific applications. Following the idea of Approximate Computing, we allow imprecision in the final result in order to utilize the sparsity of the input matrix and to allow massively parallel execution. For an n x n matrix, the proposed algorithm allows to distribute the calculations over n nodes with only little communication overhead. The result matrix exhibits the same sparsity pattern as the input matrix, allowing for efficient reuse of allocated data structures.
We evaluate the algorithm with respect to the error that it introduces into calculated results, as well as its performance and scalability. We demonstrate that the error is relatively limited for well-conditioned matrices and that results are still valuable for error-resilient applications like preconditioning even for ill-conditioned matrices. We discuss the execution time and scaling of the algorithm on a theoretical level and present a distributed implementation of the algorithm using MPI and OpenMP. We demonstrate the scalability of this implementation by running it on a high-performance compute cluster comprised of 1024 CPU cores, showing a speedup of 665x compared to single-threaded execution.
AU - Lass, Michael
AU - Mohr, Stephan
AU - Wiebeler, Hendrik
AU - Kühne, Thomas
AU - Plessl, Christian
ID - 1590
KW - approximate computing
KW - linear algebra
KW - matrix inversion
KW - matrix p-th roots
KW - numeric algorithm
KW - parallel computing
SN - 978-1-4503-5891-0/18/07
T2 - Proc. Platform for Advanced Scientific Computing (PASC) Conference
TI - A Massively Parallel Algorithm for the Approximate Calculation of Inverse p-th Roots of Large Sparse Matrices
ER -
TY - CONF
AU - Riebler, Heinrich
AU - Vaz, Gavin Francis
AU - Kenter, Tobias
AU - Plessl, Christian
ID - 1204
KW - htrop
SN - 9781450349826
T2 - Proc. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP)
TI - Automated Code Acceleration Targeting Heterogeneous OpenCL Devices
ER -
TY - CONF
AB - The exploration of FPGAs as accelerators for scientific simulations has so far mostly been focused on small kernels of methods working on regular data structures, for example in the form of stencil computations for finite difference methods. In computational sciences, often more advanced methods are employed that promise better stability, convergence, locality and scaling. Unstructured meshes are shown to be more effective and more accurate, compared to regular grids, in representing computation domains of various shapes. Using unstructured meshes, the discontinuous Galerkin method preserves the ability to perform explicit local update operations for simulations in the time domain. In this work, we investigate FPGAs as target platform for an implementation of the nodal discontinuous Galerkin method to find time-domain solutions of Maxwell's equations in an unstructured mesh. When maximizing data reuse and fitting constant coefficients into suitably partitioned on-chip memory, high computational intensity allows us to implement and feed wide data paths with hundreds of floating point operators. By decoupling off-chip memory accesses from the computations, high memory bandwidth can be sustained, even for the irregular access pattern required by parts of the application. Using the Intel/Altera OpenCL SDK for FPGAs, we present different implementation variants for different polynomial orders of the method. In different phases of the algorithm, either computational or bandwidth limits of the Arria 10 platform are almost reached, thus outperforming a highly multithreaded CPU implementation by around 2x.
AU - Kenter, Tobias
AU - Mahale, Gopinath
AU - Alhaddad, Samer
AU - Grynko, Yevgen
AU - Schmitt, Christian
AU - Afzal, Ayesha
AU - Hannig, Frank
AU - Förstner, Jens
AU - Plessl, Christian
ID - 1588
KW - tet_topic_hpc
T2 - Proc. Int. Symp. on Field-Programmable Custom Computing Machines (FCCM)
TI - OpenCL-based FPGA Design to Accelerate the Nodal Discontinuous Galerkin Method for Unstructured Meshes
ER -
TY - CONF
AU - Kenter, Tobias
AU - Förstner, Jens
AU - Plessl, Christian
ID - 1592
KW - tet_topic_hpc
T2 - Proc. Int. Conf. on Field Programmable Logic and Applications (FPL)
TI - Flexible FPGA design for FDTD using OpenCL
ER -
TY - CONF
AB - Version Control Systems (VCS) are a valuable tool for software development
and document management. Both client/server and distributed (Peer-to-Peer)
models exist, with the latter (e.g., Git and Mercurial) becoming
increasingly popular. Their distributed nature introduces complications,
especially concerning security: it is hard to control the dissemination of
contents stored in distributed VCS as they rely on replication of complete
repositories to any involved user.
We overcome this issue by designing and implementing a concept for
cryptography-enforced access control which is transparent to the user. Use
of field-tested schemes (end-to-end encryption, digital signatures) allows
for strong security, while adoption of convergent encryption and
content-defined chunking retains storage efficiency. The concept is
seamlessly integrated into Mercurial---respecting its distributed storage
concept---to ensure practical usability and compatibility to existing
deployments.
AU - Lass, Michael
AU - Leibenger, Dominik
AU - Sorge, Christoph
ID - 19
KW - access control
KW - distributed version control systems
KW - mercurial
KW - peer-to-peer
KW - convergent encryption
KW - confidentiality
KW - authenticity
SN - 978-1-5090-2054-6
T2 - Proc. 41st Conference on Local Computer Networks (LCN)
TI - Confidentiality and Authenticity for Distributed Version Control Systems - A Mercurial Extension
ER -
TY - CONF
AU - Kenter, Tobias
AU - Plessl, Christian
ID - 24
T2 - Proc. Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC)
TI - Microdisk Cavity FDTD Simulation on FPGA using OpenCL
ER -
TY - CONF
AU - Dellnitz, Michael
AU - Eckstein, Julian
AU - Flaßkamp, Kathrin
AU - Friedel, Patrick
AU - Horenkamp, Christian
AU - Köhler, Ulrich
AU - Ober-Blöbaum, Sina
AU - Peitz, Sebastian
AU - Tiemeyer, Sebastian
ID - 34
SN - 2212-0173
T2 - Progress in Industrial Mathematics at ECMI
TI - Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control
VL - 22
ER -