Computational aspects of nuclear coupled-cluster theory

We discuss computational aspects of the spherical coupled-cluster method specific to the nuclear many-body problem. Using chiral nucleon-nucleon interaction at next-to-next-to-next-to leading order (N3LO) with cutoff Lambda = 500MeV, we present coupled-cluster results for the ground state of 40Ca. Scaling and performance studies are presented together with challenges we meet with when extending the coupled-cluster effort to nuclei mass hundred and beyond.Comment: 9 pages, 5 figures, Proceedings for YKIS2011 Symposiu

A new puzzle for random interaction

We continue a series of numerical experiments on many-body systems with random two-body interactions, by examining correlations in ratios in excitation energies of yrast $J$ = 0, 2, 4, 6, 8 states. Previous studies, limited only to $J$ = 0,2,4 states, had shown strong correlations in boson systems but not fermion systems. By including $J \ge 6$ states and considering different scatter plots, strong and realistic correlations appear in both boson and fermion systems. Such correlations are a challenge to explanations of random interactions.Comment: 4 pages, 4 figure

Evaluating the Potential of Disaggregated Memory Systems for HPC applications

Disaggregated memory is a promising approach that addresses the limitations of traditional memory architectures by enabling memory to be decoupled from compute nodes and shared across a data center. Cloud platforms have deployed such systems to improve overall system memory utilization, but performance can vary across workloads. High-performance computing (HPC) is crucial in scientific and engineering applications, where HPC machines also face the issue of underutilized memory. As a result, improving system memory utilization while understanding workload performance is essential for HPC operators. Therefore, learning the potential of a disaggregated memory system before deployment is a critical step. This paper proposes a methodology for exploring the design space of a disaggregated memory system. It incorporates key metrics that affect performance on disaggregated memory systems: memory capacity, local and remote memory access ratio, injection bandwidth, and bisection bandwidth, providing an intuitive approach to guide machine configurations based on technology trends and workload characteristics. We apply our methodology to analyze thirteen diverse workloads, including AI training, data analysis, genomics, protein, fusion, atomic nuclei, and traditional HPC bookends. Our methodology demonstrates the ability to comprehend the potential and pitfalls of a disaggregated memory system and provides motivation for machine configurations. Our results show that eleven of our thirteen applications can leverage injection bandwidth disaggregated memory without affecting performance, while one pays a rack bisection bandwidth penalty and two pay the system-wide bisection bandwidth penalty. In addition, we also show that intra-rack memory disaggregation would meet the application's memory requirement and provide enough remote memory bandwidth.Comment: The submission builds on the following conference paper: N. Ding, S. Williams, H.A. Nam, et al. Methodology for Evaluating the Potential of Disaggregated Memory Systems,2nd International Workshop on RESource DISaggregation in High-Performance Computing (RESDIS), November 18, 2022. It is now submitted to the CCPE journal for revie

Alterations of lipid-related genes during anti-tuberculosis treatment: insights into host immune responses and potential transcriptional biomarkers

BackgroundThe optimal diagnosis and treatment of tuberculosis (TB) are challenging due to underdiagnosis and inadequate treatment monitoring. Lipid-related genes are crucial components of the host immune response in TB. However, their dynamic expression and potential usefulness for monitoring response to anti-TB treatment are unclear. MethodologyIn the present study, we used a targeted, knowledge-based approach to investigate the expression of lipid-related genes during anti-TB treatment and their potential use as biomarkers of treatment response. Results and discussionThe expression levels of 10 genes (ARPC5, ACSL4, PLD4, LIPA, CHMP2B, RAB5A, GABARAPL2, PLA2G4A, MBOAT2, and MBOAT1) were significantly altered during standard anti-TB treatment. We evaluated the potential usefulness of this 10-lipid-gene signature for TB diagnosis and treatment monitoring in various clinical scenarios across multiple populations. We also compared this signature with other transcriptomic signatures. The 10-lipid-gene signature could distinguish patients with TB from those with latent tuberculosis infection and non-TB controls (area under the receiver operating characteristic curve > 0.7 for most cases); it could also be useful for monitoring response to anti-TB treatment. Although the performance of the new signature was not better than that of previous signatures (i.e., RISK6, Sambarey10, Long10), our results suggest the usefulness of metabolism-centric biomarkersConclusionsLipid-related genes play significant roles in TB pathophysiology and host immune responses. Furthermore, transcriptomic signatures related to the immune response and lipid-related gene may be useful for TB diagnosis and treatment monitoring

Taurodeoxycholate Increases the Number of Myeloid-Derived Suppressor Cells That Ameliorate Sepsis in Mice

Bile acids (BAs) control metabolism and inflammation by interacting with several receptors. Here, we report that intravenous infusion of taurodeoxycholate (TDCA) decreases serum pro-inflammatory cytokines, normalizes hypotension, protects against renal injury, and prolongs mouse survival during sepsis. TDCA increases the number of granulocytic myeloid-derived suppressor cells (MDSCLT) distinctive from MDSCs obtained without TDCA treatment (MDSCL) in the spleen of septic mice. FACS-sorted MDSCLT cells suppress T-cell proliferation and confer protection against sepsis when adoptively transferred better than MDSCL. Proteogenomic analysis indicated that TDCA controls chromatin silencing, alternative splicing, and translation of the immune proteome of MDSCLT, which increases the expression of anti-inflammatory molecules such as oncostatin, lactoferrin and CD244. TDCA also decreases the expression of pro-inflammatory molecules such as neutrophil elastase. These findings suggest that TDCA globally edits the proteome to increase the number of MDSCLT cells and affect their immune-regulatory functions to resolve systemic inflammation during sepsis