Collaborative Research: PPoSS: LARGE: Panorama: Integrated Rack-Scale Acceleration for Computational Pangenomics

半导体技术的扩展正在放缓，因此，计算机系统必须越来越多地依赖于通用和专用计算引擎的异质混合。与此同时，计算机用户正在处理大量数据集的新问题，这些数据集必须以不规则和快速变化的方式进行操作，同时保持严格的隐私保障。如何有效地支持大的、稀疏的、动态的和私有的数据来解决异构系统上的大型复杂问题是软件/硬件系统研究的重大挑战之一。为了应对这一重大挑战，全景项目正在探索计算泛基因组学的集成机架级加速。集成机架级加速是指一种新兴的计算机系统范例，它使用数十个紧密集成的计算节点，每个节点都包括通用处理器和专用加速器的混合，这些加速器与专用网络相互连接。计算泛基因组学指的是最近出现的一种趋势，即将基因组（生物体的遗传物质）表示为一个DNA碱基对的单一线性序列，而是作为一个复杂的序列网络，有效地同时表示许多个体基因组之间的关系。计算泛基因组学自然地抓住了大、稀疏、动态和私有数据的趋势，因此是探索异构软件/硬件系统研究的完美应用领域。该项目的新颖之处在于：真正的跨堆栈方法跨越应用程序，编程语言，编译器，架构，安全性和隐私，包括使用独一无二的全景原型系统；加速特定领域计算和统一异构系统的新硬件技术；新的软件技术使程序员能够利用异构系统的性能优势；新的软件/硬件技术使这种异构系统更加安全。该项目的影响是：具体来说，使计算生物学家能够更好地看到迄今为止一直隐藏的全民基因组学的“遗传暗物质”，从而开辟新的科学发现；更广泛地使未来的计算机用户能够更容易地利用异构计算机系统来解决大型和复杂的问题。该项目还在推行两项影响范围更广的倡议。首先是一项雄心勃勃但具体的举措，通过为一个新的为期四周的暑期项目开发一个低水平的计算机系统模块，增加少数族裔学生对计算机科学的参与，该项目针对的是即将升入大学二年级的学生。第二个涉及具体计划，在计算生物学和计算机系统社区中发展开源软件/硬件生态系统。全景项目包括一个高度跨学科的研究团队，横跨四个重点领域：应用程序（计算生物学）、编程语言和编译器、计算机体系结构和安全与隐私。该团队正在采用整体软件/硬件协同设计方法来探索五个紧密相连的研究重点。前三个推力是在计算堆栈上自上而下构建的。Thrust 1研究新的计算泛基因组学数据结构和算法，并将开发panbench，这是一个适用于驱动剩余推力的新基准套件。推力2研究新的编程语言和编译器技术。Thrust 3研究了新的计算机体系结构，支持具有1M+核的全机架多核、分区的全局地址空间、基于统一阵列的加速器和用于计算泛基因组学的特定应用加速器芯片。最后两个重点涉及软件和硬件。推力4研究了新的安全和隐私技术，包括异构机架规模系统上的可扩展安全计算，具有自动调优的安全机架规模资源管理，以及泛基因组学的差分隐私和同态加密。推力5包括通过使用独一无二的全景原型系统对其他推力的研究思路进行整体评估。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Semiconductor technology scaling is slowing, and as a consequence, computer systems must increasingly rely on a heterogeneous mix of general-purpose and specialized computing engines. At the same time, computer users are tackling new problems with massive datasets that must be manipulated in irregular and rapidly changing ways while maintaining strict privacy guarantees. Efficiently supporting big, sparse, dynamic, and private data to solve large complex problems on heterogeneous systems is one of the grand challenges in software/hardware systems research. To address this grand challenge, the Panorama project is exploring integrated rack-scale acceleration for computational pangenomics. Integrated rack-scale acceleration refers to an emerging computer-systems paradigm that uses tens of tightly integrated computing nodes, each of which includes a mix of general-purpose processors and specialized accelerators interconnected with a special-purpose network. Computational pangenomics refers to a recent trend towards representing genomes, the genetic material of an organism, not as a single linear sequence of DNA base pairs but instead as an intricate network of sequences that efficiently represents the relationships between many individuals' genomes at once. Computational pangenomics naturally captures the trend towards big, sparse, dynamic, and private data and is thus a perfect application domain to explore heterogeneous software/hardware systems research. The project's novelties are: a truly cross-stack approach spanning applications, programming languages, compilers, architecture, security, and privacy including use of a one-of-a-kind Panorama prototype system; new hardware techniques to accelerate domain-specific computing and to unify heterogeneous systems; new software techniques to let programmers harness the performance advantages of heterogeneous systems; and new software/hardware techniques to make such heterogeneous systems more secure. The project's impacts are: to specifically enable computational biologists to better see the "genetic dark matter" of population-wide genomics which has been to date hidden, opening up new scientific discoveries; and to more generally enable future computer users to more easily take advantage of heterogeneous computer systems to solve large and complex problems. This project is also pursuing two broader impact initiatives. The first is an ambitious yet concrete initiative to increase participation of under-represented minority students in computer science by developing a low-level computer-systems module for a new four-week summer program targeting rising sophomores. The second involves specific plans to grow the open-source software/hardware ecosystem in the computational-biology and computer-systems communities.The Panorama project includes a highly interdisciplinary team of researchers across four focus areas: applications (computational biology), programming languages & compilers, computer architecture, and security & privacy. The team is taking a holistic software/hardware co-design approach to explore five tightly interconnected research thrusts. The first three thrusts are structured from top-down across the computing stack. Thrust 1 investigates new computational pangenomics data structures and algorithms and will develop PanoBench, a new benchmark suite suitable for driving the remaining thrusts. Thrust 2 investigates new programming-language and compiler techniques. Thrust 3 investigates new computer architectures with support for a whole-rack manycore with 1M+ cores and a partitioned global address space, unified array-based accelerators, and application-specific accelerator chiplets for computational pangenomics. The final two thrusts cut across both software and hardware. Thrust 4 investigates new security and privacy techniques including scalable secure computation on heterogeneous rack-scale systems, secure rack-scale resource management with auto-tuning, and differential privacy and homomorphic encryption for pangenomics. Thrust 5 involves holistically evaluating the research ideas in the other thrusts through the use of a one-of-a-kind Panorama prototype system.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.