Light-Front Quantum Chromodynamics: A framework for the analysis of hadron physics

White Paper of International Light Cone Advisory CommitteeAn outstanding goal of physics is to find solutions that describe hadrons in the theory of strong interactions, Quantum Chromodynamics (QCD). For this goal, the light-front Hamiltonian formulation of QCD (LFQCD) is a complementary approach to the well-established lattice gauge method. LFQCD offers access to the hadrons' nonperturbative quark and gluon amplitudes, which are directly testable in experiments at existing and future facilities. We present an overview of the promises and challenges of LFQCD in the context of unsolved issues in QCD that require broadened and accelerated investigation. We identify specific goals of this approach and address its quantifiable uncertainties

Effects of whey protein alone or as part of a multi-ingredient formulation on strength, fat-free mass, or lean body mass in resistance-trained individuals: A meta-analysis

BACKGROUND: Even though the positive effects of whey protein-containing supplements for optimizing the anabolic responses and adaptations process in resistance-trained individuals have been supported by several investigations, their use continues to be controversial. Additionally, the administration of different multi-ingredient formulations where whey proteins are combined with carbohydrates, other protein sources, creatine, and amino acids or derivatives, has been extensively proposed as an effective strategy to maximize strength and muscle mass gains in athletes. OBJECTIVE: We aimed to systematically summarize and quantify whether whey protein-containing supplements, administered alone or as a part of a multi-ingredient, could improve the effects of resistance training on fat-free mass or lean body mass, and strength in resistance-trained individuals when compared with other iso-energetic supplements containing carbohydrates or other sources of proteins. METHODS: A structured literature search was conducted on PubMed, Science Direct, Web of Science, Cochrane Libraries, US National Institutes of Health clinicaltrials.gov, SPORTDiscus, and Google Scholar databases. Main inclusion criteria comprised randomized controlled trial study design, adults (aged 18 years and over), resistance-trained individuals, interventions (a resistance training program for a period of 6 weeks or longer, combined with whey protein supplementation administered alone or as a part of a multi-ingredient), and a calorie equivalent contrast supplement from carbohydrates or other non-whey protein sources. Continuous data on fat-free mass and lean body mass, and maximal strength were pooled using a random-effects model. RESULTS: Data from nine randomized controlled trials were included, involving 11 treatments and 192 participants. Overall, with respect to the ingestion of contrast supplements, whey protein supplementation, administered alone or as part of a multi-ingredient, in combination with resistance training, was associated with small extra gains in fat-free mass or lean body mass, resulting in an effect size of g = 0.301, 95% confidence interval (CI) 0.032-0.571. Subgroup analyses showed less clear positive trends resulting in small to moderate effect size g = 0.217 (95% CI -0.113 to 0.547) and g = 0.468 (95% CI 0.003-0.934) in favor of whey and multi-ingredient, respectively. Additionally, a positive overall extra effect was also observed to maximize lower (g = 0.316, 95% CI 0.045-0.588) and upper body maximal strength (g = 0.458, 95% CI 0.161-0.755). Subgroup analyses showed smaller superiority to maximize strength gains with respect to the contrast groups for lower body (whey protein: g = 0.343, 95% CI -0.016 to 0.702, multi-ingredient: g = 0.281, 95% CI -0.135 to 0.697) while in the upper body, multi-ingredient (g = 0.612, 95% CI 0.157-1.068) seemed to produce more clear effects than whey protein alone (g = 0.343, 95% CI -0.048 to 0.735). LIMITATIONS: Studies involving interventions of more than 6 weeks on resistance-training individuals are scarce and account for a small number of participants. Furthermore, no studies with an intervention longer than 12 weeks have been found. The variation regarding the supplementation protocol, namely the different doses criteria or timing of ingestion also add some concerns to the studies comparison. CONCLUSIONS: Whey protein alone or as a part of a multi-ingredient appears to maximize lean body mass or fat-free mass gain, as well as upper and lower body strength improvement with respect to the ingestion of an iso-energetic equivalent carbohydrate or non-whey protein supplement in resistance-training individuals. This enhancement effect seems to be more evident when whey proteins are consumed within a multi-ingredient containing creatine

Accelerating nuclear configuration interaction calculations through a preconditioned block iterative eigensolver

We describe a number of recently developed techniques for improving the performance of large-scale nuclear configuration interaction calculations on high performance parallel computers. We show the benefit of using a preconditioned block iterative method to replace the Lanczos algorithm that has traditionally been used to perform this type of computation. The rapid convergence of the block iterative method is achieved by a proper choice of starting guesses of the eigenvectors and the construction of an effective preconditioner. These acceleration techniques take advantage of special structure of the nuclear configuration interaction problem which we discuss in detail. The use of a block method also allows us to improve the concurrency of the computation, and take advantage of the memory hierarchy of modern microprocessors to increase the arithmetic intensity of the computation relative to data movement. We also discuss the implementation details that are critical to achieving high performance on massively parallel multi-core supercomputers, and demonstrate that the new block iterative solver is two to three times faster than the Lanczos based algorithm for problems of moderate sizes on a Cray XC30 system

Accelerating nuclear configuration interaction calculations through a preconditioned block iterative eigensolver

We describe a number of recently developed techniques for improving the performance of large-scale nuclear configuration interaction calculations on high performance parallel computers. We show the benefit of using a preconditioned block iterative method to replace the Lanczos algorithm that has traditionally been used to perform this type of computation. The rapid convergence of the block iterative method is achieved by a proper choice of starting guesses of the eigenvectors and the construction of an effective preconditioner. These acceleration techniques take advantage of special structure of the nuclear configuration interaction problem which we discuss in detail. The use of a block method also allows us to improve the concurrency of the computation, and take advantage of the memory hierarchy of modern microprocessors to increase the arithmetic intensity of the computation relative to data movement. We also discuss the implementation details that are critical to achieving high performance on massively parallel multi-core supercomputers, and demonstrate that the new block iterative solver is two to three times faster than the Lanczos based algorithm for problems of moderate sizes on a Cray XC30 system

A high performance block eigensolver for nuclear Configuration Interaction calculations

As on-node parallelism increases and the performance gap between the processor and the memory system widens, achieving high performance in large-scale scientific applications requires an architecture-aware design of algorithms and solvers. We focus on the eigenvalue problem arising in nuclear Configuration Interaction (CI) calculations, where a few extreme eigenpairs of a sparse symmetric matrix are needed. We consider a block iterative eigensolver whose main computational kernels are the multiplication of a sparse matrix with multiple vectors (SpMM), and tall-skinny matrix operations. We present techniques to significantly improve the SpMM and the transpose operation SpMM by using the compressed sparse blocks (CSB) format. We achieve 3-4× speedup on the requisite operations over good implementations with the commonly used compressed sparse row (CSR) format. We develop a performance model that allows us to correctly estimate the performance of our SpMM kernel implementations, and we identify cache bandwidth as a potential performance bottleneck beyond DRAM. We also analyze and optimize the performance of LOBPCG kernels (inner product and linear combinations on multiple vectors) and show up to 15× speedup over using high performance BLAS libraries for these operations. The resulting high performance LOBPCG solver achieves 1.4× to 1.8× speedup over the existing Lanczos solver on a series of CI computations on high-end multicore architectures (Intel Xeons). We also analyze the performance of our techniques on an Intel Xeon Phi Knights Corner (KNC) processor.