EAGER: CDS&E: Field Programmable Gate Arrays (FPGAs) for Enhancing the Speed and Energy Efficiency of Quantum Chemistry Simulations

Bryan M.加州大学河滨分校的Wong得到了化学系化学理论、模型和计算方法项目的支持，利用新的计算硬件，即现场可编程门阵列（FPGA）。 该研究项目的目标是提高量子化学计算的速度和能源效率。 现代量子化学计算严重依赖于大规模并行计算硬件来实现其预测。大规模并行是指使用大量独立的计算机（或计算机处理器）同时执行一组协调计算的术语。这种计算的定量准确预测影响了几种化学技术，包括燃烧，催化，过程建模和化学生产行业。然而，用于运行这些预测计算的超级计算中心消耗了大量的能源和资源。 而且，随着所研究的化学系统越来越大，许多这样的计算不能很好地扩展。为了解决这些重要问题，FPGA被用来提高计算速度，并在大规模量子计算中保持性能和能效之间的微妙平衡。除了解决这些科学和技术的需求，这个项目是在加州大学河滨分校，这是一个认可的西班牙裔服务机构（HSI）进行。 因此，黄教授的院校是吸引研究人员的理想地方，否则他们可能不知道科学和工程的就业机会。 FPGA由数千个连接和逻辑块组成，这些连接和逻辑块彼此无缝连接，以创建可重新配置的编程单元。与图形处理单元（GPU）一样，FPGA是并行化的理想选择，但其额外优势是在硬件级别具有可重编程电路，以实现进一步的并行化和显著的能量增益。这个EAGER项目被细分为两个主要的（但高度相关的）目标。推力1将扩展FPGA的使用，以加速Fock矩阵构建和哈密顿对角化，分别用于从头算分子动力学（AIMD）和线性响应时间依赖密度泛函理论计算。Thrust 2随后将评估和展示FPGA在这些量子计算中的巨大能效（与CPU/GPU相比）。量子化学领域尚未将FPGA用于任何类型的生产级计算，这为该领域的变革性领导创造了令人兴奋的机会。这些目标共同解决了量子化学中的基本（但实际）并行化问题，并采用非传统计算方法，引入了一种新的计算能力，以节能的方式执行这些量子化学计算。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Professor Bryan M. Wong of the University of California-Riverside is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to utilize new computational hardware, known as Field Programmable Gate Arrays (FPGAs). The goal of this research project is to enhance the speed and energy efficiency of quantum chemistry calculations. Modern quantum chemistry calculations depend critically on massively parallelized computational hardware to enable their predictions. Massively parallel is the term for using a large number of separate computers (or computer processors) to perform a set of coordinated computations simultaneously. Quantitatively accurate predictions from such calculations impact several chemical technologies including combustion, catalysis, process modeling, and chemical production industries. However, the supercomputing centers used to run these predictive calculations consume enormous amounts of energy and resources. Also many such calculations do not scale well as the studied chemical systems grow larger. To address these important issues, FPGAs are being harnessed to enhance the computational speed, as well as to maintain the delicate balance between performance and energy efficiency for large-scale quantum calculations. In addition to addressing these scientific and technological needs, this project is carried out at the University of California-Riverside, which is an accredited Hispanic Serving Institution (HSI). As such, Professor Wong's institution is an ideal place to attract researchers who might otherwise not be aware of the employment opportunities in science and engineering. An FPGA consists of an array of thousands of connection and logic blocks seamlessly connected with each other to create extremely re-configurable programming units. Like Graphics Processing Units (GPUs), FPGAs are ideal for parallelization, but with the added advantage of having reprogrammable circuitry at the hardware level to enable even further parallelization and significant energy gains. This EAGER project is sub-divided into two main (but highly connected) thrusts. Thrust 1 will extend the use of FPGAs to accelerate Fock-matrix builds and Hamiltonian diagonalization for ab initio molecular dynamics (AIMD) and linear-response time-dependent density functional theory calculations, respectively. Thrust 2 will subsequently assess and demonstrate the immense energy efficiency (compared to CPUs/GPUs) of FPGAs for these quantum calculations. The field of quantum chemistry has yet to utilize FPGAs for production-level calculations of any kind, creating an exciting opportunity for transformative leadership in this area. Together these thrusts address basic (yet practical) parallelization issues in quantum chemistry with non-conventional computing approaches, and introduce a new computational capability to perform these quantum chemistry calculations in an energy-efficient manner.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.