On-the-fly Race Detection for Programs with Recursive Spawn-Sync Parallelism

Detecting data race is very important for debugging shared-memory parallel programs, because data races result in unintended nondeterministic execution of the program. We propose a dynamic on-the-fly race detection mechanism called Parallel Nondeterminator to check for determinacy races during the parallel execution of a program with recursive spawn-sync parallelism. A modified version of Nested Region Labeling scheme is developed for the concurrency relationship test in the spawn-sync parallel structure. Through the identification of Least Common Ancestor in the spawn tree, the Parallel Nondeterminator only needs to keep two read access records and one write access record for each shared location. The work and critical path in the instrumented codes are analyzed as well as time complexity and space requirements. Let N denote the maximum depth of the recursion in the parallel program. The worst case time increased for each spawn and sync operation is O(N) and the time required to monitor any shared memory location is O(lgN). Moreover, Parallel Nondeterminator is able to execute the race detection code without loss of parallelism of the original program. In summary, the Parallel Non-determinator represents a provably efficient strategy for detecting data races for shared-memory parallel programs.Singapore-MIT Alliance (SMA

ZeRO++: Extremely Efficient Collective Communication for Giant Model Training

Zero Redundancy Optimizer (ZeRO) has been used to train a wide range of large language models on massive GPUs clusters due to its ease of use, efficiency, and good scalability. However, when training on low-bandwidth clusters, or at scale which forces batch size per GPU to be small, ZeRO's effective throughput is limited because of high communication volume from gathering weights in forward pass, backward pass, and averaging gradients. This paper introduces three communication volume reduction techniques, which we collectively refer to as ZeRO++, targeting each of the communication collectives in ZeRO. First is block-quantization based all-gather. Second is data remapping that trades-off communication for more memory. Third is a novel all-to-all based quantized gradient averaging paradigm as replacement of reduce-scatter collective, which preserves accuracy despite communicating low precision data. Collectively, ZeRO++ reduces communication volume of ZeRO by 4x, enabling up to 2.16x better throughput at 384 GPU scale.Comment: 12 page

The connection between tricarboxylic acid cycle enzyme mutations and pseudohypoxic signaling in pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from chromaffin cells, holding significant clinical importance due to their capacity for excessive catecholamine secretion and associated cardiovascular complications. Roughly 80% of cases are associated with genetic mutations. Based on the functionality of these mutated genes, PPGLs can be categorized into distinct molecular clusters: the pseudohypoxia signaling cluster (Cluster-1), the kinase signaling cluster (Cluster-2), and the WNT signaling cluster (Cluster-3). A pivotal factor in the pathogenesis of PPGLs is hypoxia-inducible factor-2α (HIF2α), which becomes upregulated even under normoxic conditions, activating downstream transcriptional processes associated with pseudohypoxia. This adaptation provides tumor cells with a growth advantage and enhances their ability to thrive in adverse microenvironments. Moreover, pseudohypoxia disrupts immune cell communication, leading to the development of an immunosuppressive tumor microenvironment. Within Cluster-1a, metabolic perturbations are particularly pronounced. Mutations in enzymes associated with the tricarboxylic acid (TCA) cycle, such as succinate dehydrogenase (SDHx), fumarate hydratase (FH), isocitrate dehydrogenase (IDH), and malate dehydrogenase type 2 (MDH2), result in the accumulation of critical oncogenic metabolic intermediates. Notable among these intermediates are succinate, fumarate, and 2-hydroxyglutarate (2-HG), which promote activation of the HIFs signaling pathway through various mechanisms, thus inducing pseudohypoxia and facilitating tumorigenesis. SDHx mutations are prevalent in PPGLs, disrupting mitochondrial function and causing succinate accumulation, which competitively inhibits α-ketoglutarate-dependent dioxygenases. Consequently, this leads to global hypermethylation, epigenetic changes, and activation of HIFs. In FH-deficient cells, fumarate accumulation leads to protein succination, impacting cell function. FH mutations also trigger metabolic reprogramming towards glycolysis and lactate synthesis. IDH1/2 mutations generate D-2HG, inhibiting α-ketoglutarate-dependent dioxygenases and stabilizing HIFs. Similarly, MDH2 mutations are associated with HIF stability and pseudohypoxic response. Understanding the intricate relationship between metabolic enzyme mutations in the TCA cycle and pseudohypoxic signaling is crucial for unraveling the pathogenesis of PPGLs and developing targeted therapies. This knowledge enhances our comprehension of the pivotal role of cellular metabolism in PPGLs and holds implications for potential therapeutic advancements

Colossal Magnetoresistance in Twisted Intertwined Graphene Spirals

Colossal magnetoresistance (CMR) is highly applicable in spintronic devices such as magnetic sensors, magnetic memory, and hard drives. Typically, CMR is found in Weyl semimetals characterized by perfect electron-hole symmetry or exceptionally high electric conductivity and mobility. Our study explores this phenomenon in a recently developed graphene moir$\acute{e}$ system, which demonstrates CMR owing to its topological structure and high-quality crystal formation. We specifically investigate the electronic properties of three-dimensional (3D) intertwined twisted graphene spirals (TGS), manipulating the screw dislocation axis to achieve a rotation angle of 7.3$^{\circ}$. Notably, at 14 T and 2 K, the magnetoresistance of these structures reached 1.7$\times$10$^7$%, accompanied by an unexpected metal-to-insulator transition as the temperature increased. This transition becomes noticeable when the magnetic field exceeds a minimal threshold of approximately 0.1 T. These observations suggest the existence of complex, correlated states within the partially filled three-dimensional Landau levels of the 3D TGS system. Our findings open up new possibilities for achieving CMR by engineering the topological structure of 2D layered moir$\acute{e}$ systems

KRT6A Promotes Lung Cancer Cell Growth and Invasion Through MYC-Regulated Pentose Phosphate Pathway

Keratin 6A (KRT6A) belongs to the keratin protein family which is a critical component of cytoskeleton in mammalian cells. Although KRT6A upregulation in non-small cell lung cancer (NSCLC) has been reported, the regulatory mechanism and functional role of KRT6A in NSCLC development have been less well investigated. In this study, KRT6A was confirmed to be highly expressed in NSCLC tissue samples, and its high expression correlated with poor patient prognosis. Furthermore, overexpression of KRT6A promotes NSCLC cell proliferation and invasion. Mechanistically, KRT6A overexpression is sufficient to upregulate glucose-6-phosphate dehydrogenase (G6PD) levels and increase the pentose phosphate pathway flux, an essential metabolic pathway to support cancer cell growth and invasion. In addition, we discovered that lysine-specific demethylase 1A (LSD1) functions upstream to promote KRT6A gene expression. We also found that the MYC family members c-MYC/MYCN are involved in KRT6A-induced G6PD upregulation. Therefore, this study reveals an underappreciated mechanism that KRT6A acts downstream of LSD1 and functions as a pivotal driver for NSCLC progression by upregulating G6PD through the MYC signaling pathway. Together, KRT6A and LSD1 may serve as potential prognostic indictors and therapeutic targets for NSCLC

Simultaneous removal of cadmium and nitrate in aqueous media by nanoscale zerovalent iron (nZVI) and Au doped nZVI particles

Nanoscale zerovalent iron (nZVI) has demonstrated high efficacy for treating nitrate or cadmium (Cd) contamination, but its efficiency for simultaneous removal of nitrate and Cd has not been investigated. This study evaluated the reactivity of nZVI to the co-contaminants and by-product formation, employed different catalysts to reduce nitrite yield from nitrate, and examined the transformation of nZVI after reaction. Nitrate reduction resulted in high solution pH, negatively charged surface of nZVI, formation of Fe3O4 (a stable transformation of nZVI), and no release of ionic iron. Increased pH and negative charge contributed to significant increase in Cd(II) removal capacity (from 40 mg/g to 188 mg/g) with nitrate present. In addition, nitrate reduction by nZVI could be catalyzed by Cd(II): while 30% of nitrate was reduced by nZVI within 2 h in the absence of Cd(II), complete nitrate reduction was observed in the presence of 40 mg-Cd/L due to the formation of Cd islands (Cd(0) and CdO) on the nZVI particles. While nitrate was reduced mostly to ammonium when Cd(II) was not present or at Cd(II) concentrations ≥ 40 mg/L, up to 20% of the initial nitrate was reduced to nitrite at Cd(II) concentrations < 40 mg/L. Among nZVI particles doped with 1 wt. % Cu, Ag, or Au, nZVI deposited with 1 wt. % Au reduced nitrite yield to less than 3% of the initial nitrate, while maintaining a high Cd(II) removal capacity

Heteroaggregation of nanoparticles with biocolloids and geocolloids

The application of nanoparticles has raised concern over the safety of these materials to human health and the ecosystem. After release into an aquatic environment, nanoparticles are likely to experience heteroaggregation with biocolloids, geocolloids, natural organic matter (NOM) and other types of nanoparticles. Heteroaggregation is of vital importance for determining the fate and transport of nanoparticles in aqueous phase and sediments. In this article, we review the typical cases of heteroaggregation between nanoparticles and biocolloids and/or geocolloids, mechanisms, modeling, and important indicators used to determine heteroaggregation in aqueous phase. The major mechanisms of heteroaggregation include electric force, bridging, hydrogen bonding, and chemical bonding. The modeling of heteroaggregation typically considers DLVO, X-DLVO, and fractal dimension. The major indicators for studying heteroaggregation of nanoparticles include surface charge measurements, size measurements, observation of morphology of particles and aggregates, and heteroaggregation rate determination. In the end, we summarize the research challenges and perspective for the heteroaggregation of nanoparticles, such as the determination of αhetero values and heteroaggregation rates; more accurate analytical methods instead of DLS for heteroaggregation measurements; sensitive analytical techniques to measure low concentrations of nanoparticles in heteroaggregation systems; appropriate characterization of NOM at the molecular level to understand the structures and fractionation of NOM; effects of different types, concentrations, and fractions of NOM on the heteroaggregation of nanoparticles; the quantitative adsorption and desorption of NOM onto the surface of nanoparticles and heteroaggregates; and a better understanding of the fundamental mechanisms and modeling of heteroaggregation in natural water which is a complex system containing NOM, nanoparticles, biocolloids and geocolloids

Parallel Nondeterminator

A report submitted for the cours