With the exponential growth of high-fidelity sensor and simulated data, the scientific community is increasingly reliant on ultrascale HPC resources to handle its data analysis requirements. However, to use such extreme computing power effectively, the I/O components must be designed in a balanced fashion, as any architectural bottleneck will quickly render the platform intolerably inefficient. To understand I/O performance of data-intensive applications in realistic computational settings, we develop a lightweight, portable benchmark called MADbench2, which is derived directly from a large-scale Cosmic Microwave Background (CMB) data analysis package. Our study represents one of the most comprehensive I/O analyses of modern parallel file systems, examining a broad range of system architectures and configurations, including Lustre on the Cray XT3, XT4, and Intel Itanium2 clusters; GPFS on IBM Power5 and AMD Opteron platforms; a BlueGene/P installation using GPFS and PVFS2 file systems; and CXFS on the SGI Altix\-3700. We present extensive synchronous I/O performance data comparing a number of key parameters including concurrency, POSIX- versus MPI-IO, and unique-versus shared-file accesses, using both the default environment as well as highly-tuned I/O parameters. Finally, we explore the potential of asynchronous I/O and show that only the two of the nine evaluated systems benefited from MPI-2's asynchronous MPI-IO. On those systems, experimental results indicate that the computational intensity required to hide I/O effectively is already close to the practical limit of BLAS3 calculations. Overall, our study quantifies vast differences in performance and functionality of parallel file systems across state-of-the-art platforms -- showing I/O rates that vary up to 75x on the examined architectures -- while providing system designers and computational scientists a lightweight tool for conducting further analysis.

In this dissertation, I briefly go through my subject areas—from Astrophysics, Cosmology, to Cosmic Microwave Background (CMB) radiation; and Data Science & High-Performance Computing. I go through the beginning of the Universe briefly in part I and introduce the Physics of the CMB in part II. Then I move on to how it can be observed experimentally, mathematically, and computationally in part III. In parts IV to VI, I write about 2 specific CMB experiments—POLARBEAR & LiteBIRD, together with my research involved in them.In part V, an original research on a measurement of the CMB ?-mode at sub-degree scales is presented using the 3rd–5th seasons of POLARBEAR observations. This demonstrates the capability of a single medium aperture telescope with a Continuously Rotating Half-Wave Plate (CRHWP) to target both the low-l and high-l ?-mode science at 50 ≤ l ≤ 3000. In part VI, the effect of detector crosstalk systematics on the CMB power-spectra is studied in detailed in the example of the LiteBIRD experiment. An analytical, map-domain solution is developed, a computational simulation method is implemented, and the two predictions are compared using the LiteBIRD experiment design specification. The general agreement of the two shows that the analytical model well describes the LiteBIRD experiment, and can be used to calculate the systematic effects without performing time-consuming time-domain simulations with high degree of accuracy. This can be used to forecast the amount of crosstalk systematics and to develop mitigation strategies. A mitigation strategy is presented, which is a hardware-based mitigation method that minimizes the crosstalk systematic effects in the 2pt power-spectra. While the author claims that this dissertation is original, unpublished, and is an independent work, only those in parts V and VI are original research. Other materials in parts I to IV are introductory materials summarizing well-known knowledge in the field. In particular, many plots, graphs and visualizations from these parts are from existing publications which should fall under “fair use” and are properly cited. There are a few exceptions that images are obtained through internal circulations including presentations from others in the collaborations where original source is not known. This is documented in sec. 38.6.

The Cosmic Microwave Background (CMB) is an exquisitely sensitive probe of the fundamental parameters of cosmology. Extracting this information is computationally intensive, requiring massively parallel computing and sophisticated numerical algorithms. In this work we present MAD bench, a lightweight version of the MADCAP CMB power spectrum estimation code that retains the operational complexity and integrated system requirements. In addition, to quantify communication behavior across a variety of architectural platforms, we introduce the Integrated Performance Monitoring (IPM) package: a portable, lightweight, and scalable tool for effectively extracting MPI message-passing over heads. A performance characterization study is conducted on some of the world's most powerful supercomputers, including the superscalar Seaborg (IBMPower3+) and CC-NUMA Columbia (SGI Altix), as well as the vector-based Earth Simulator (NEC SX-6 enhanced) and Phoenix (Cray X1) systems. In-depth analysis shows that in order to bridge the gap between theoretical and sustained system performance, it is critical to gain a clear understanding of how the distinct parts of large-scale parallel applications interact with the individual subcomponents of HEC platforms.

The last decade has witnessed a rapid proliferation of superscalar cache-based microprocessors to build high-end capability and capacity computers primarily because of their generality, scalability, and cost effectiveness. However, the recent development of massively parallel vector systems is having a significant effect on the supercomputing landscape. In this paper, we compare the performance of the recently-released Cray X1 vector system with that of the cacheless NEC SX-6 vector machine, and the superscalar cache-based IBM Power3 and Power4 architectures for scientific applications. Overall results demonstrate that the X1 is quite promising, but performance improvements are expected as the hardware, systems software, and numerical libraries mature. Code reengineering to effectively utilize the complex architecture may also lead to significant efficiency enhancements.