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Tapish Narwal

Publications and source records attributed to Tapish Narwal.

4 recordsLinked to original sources

Post-Moore Technologies for Plasma Simulation: A Community Roadmap

Plasma simulations are among the most computationally demanding scientific workloads, combining high-dimensional kinetic evolution, particle-mesh coupling, field solves, and data-intensive communication. As general-purpose processor scaling slows, post-Moore technologies are being explored to address bottlenecks in data movement, memory access, and power consumption. This paper provides a community perspective on the role of these technologies in plasma simulation, assessing three major classes: reconfigurable and data-path accelerators, non-von Neumann architectures, and quantum computing. Each is evaluated, in a co-design approach, against representative plasma workloads spanning particle-in-cell, continuum Vlasov, gyrokinetic, fluid/MHD, hybrid, and warm dense matter methods. We find that no single technology can replace existing HPC platforms. Instead, three tiers of opportunity emerge: FPGA-class and data-path accelerators offer near-term kernel offload and workflow-level data services, non-von Neumann architectures represent medium-term directions for operator-level acceleration, and quantum computing, although the least mature, is potentially the most disruptive for warm dense matter and inertial confinement fusion microphysics. We outline best practices for selective adoption and identify focused demonstrators, benchmarking, and modular software ecosystems as immediate community priorities.

cs.ET

A Parallel and Highly-Portable HPC Poisson Solver: Preconditioned Bi-CGSTAB with alpaka

This paper presents the design, implementation, and performance analysis of a parallel and GPU-accelerated Poisson solver based on the Preconditioned Bi-Conjugate Gradient Stabilized (Bi-CGSTAB) method. The implementation utilizes the MPI standard for distributed-memory parallelism, while on-node computation is handled using the alpaka framework: this ensures both shared-memory parallelism and inherent performance portability across different hardware architectures. We evaluate the solver's performances on CPUs and GPUs (NVIDIA Hopper H100 and AMD MI250X), comparing different preconditioning strategies, including Block Jacobi and Chebyshev iteration, and analyzing the performances both at single and multi-node level. The execution efficiency is characterized with a strong scaling test and using the AMD Omnitrace profiling tool. Our results indicate that a communication-free preconditioner based on the Chebyshev iteration can speed up the solver by more than six times. The solver shows comparable performances across different GPU architectures, achieving a speed-up in computation up to 50 times compared to the CPU implementation. In addition, it shows a strong scaling efficiency greater than 90% up to 64 devices.

cs.DC

Enabling High-Throughput Parallel I/O in Particle-in-Cell Monte Carlo Simulations with openPMD and Darshan I/O Monitoring

Large-scale HPC simulations of plasma dynamics in fusion devices require efficient parallel I/O to avoid slowing down the simulation and to enable the post-processing of critical information. Such complex simulations lacking parallel I/O capabilities may encounter performance bottlenecks, hindering their effectiveness in data-intensive computing tasks. In this work, we focus on introducing and enhancing the efficiency of parallel I/O operations in Particle-in-Cell Monte Carlo simulations. We first evaluate the scalability of BIT1, a massively-parallel electrostatic PIC MC code, determining its initial write throughput capabilities and performance bottlenecks using an HPC I/O performance monitoring tool, Darshan. We design and develop an adaptor to the openPMD I/O interface that allows us to stream PIC particle and field information to I/O using the BP4 backend, aggressively optimized for I/O efficiency, including the highly efficient ADIOS2 interface. Next, we explore advanced optimization techniques such as data compression, aggregation, and Lustre file striping, achieving write throughput improvements while enhancing data storage efficiency. Finally, we analyze the enhanced high-throughput parallel I/O and storage capabilities achieved through the integration of openPMD with rapid metadata extraction in BP4 format. Our study demonstrates that the integration of openPMD and advanced I/O optimizations significantly enhances BIT1's I/O performance and storage capabilities, successfully introducing high throughput parallel I/O and surpassing the capabilities of traditional file I/O.

cs.DC

Discovery of a supercluster candidate at $z \sim 1.1$

We report a promising candidate for a distant supercluster at z $\sim 1.1$ in the Dark Energy Survey Science Verification data. We examine smoothed semi-3D galaxy density maps in various photo-z slices. Among several overdense regions, in this work we report the most significant one as having a $3σ$ overdensity at a redshift of $\sim1.1$, over a $\sim160$ Mpc scale, much larger than the regular cluster scale (several Mpc). The shape of the supercluster is not circular in the sky projection. Therefore, we regard the point of maximum overdensity as the center for quantitative measurements. Two different estimates suggest the mass of the supercluster to be $1.37\substack{+1.31 \\ -0.79} \times 10^{17} M_{\odot}$, more than one order more massive than regular galaxy clusters. Except for protosuperclusters found with emission-line galaxies, this could be the most distant supercluster to date defined by regular galaxies. A spectroscopic confirmation would make this a very interesting object for cosmology. We discuss the possible implications of such a massive structure for $Λ$CDM cosmology.

astro-ph.CO