[tile] DB libraries, and large-scale graph analytics. Open-source software projects resulting from his work include the Matrix Template Library, the Boost Graph Library and Open MPI. 。Phil Ratzloff *。Distinguished relationships between elements of a data set *，Without regard to what the data set actually is *。 Graph theoretical (abstract) results can be applied to many different practical (concrete) problems -theory cvMuNKCATIOWS 有二有 灿瑟必帮 和一是/第 手太则光大 A，训四 昱 站 -本| 厅 是，主 半一司、|全之体 ~ 对 /人-看 奋才全 和 全原 和 刁曾 The Future ls Big Graph: on meetalThngs soneaiadman MD] Basic Principles *。The C++ standard library (nee STL) provides

Selection ✓ Order by ❏ Group by ✓ Query ✓ Limit ✓ Expression Compatibility ✓ Join ✓ Subquery ✓ Graph traverse ✓ Out direction ✓ In direction ✓ Bidirection ✓ Edge traverse ✓ Distinct Index 01.

Scott, Principal Engineer at CMU SEI Graph/ML/AI algorithms for large- and small- scale parallel systems. Working on GBTL, a linear algebra-based C++ library for graph analytics.[DISTRIBUTION STATEMENT GraphBLAS community, C API Overview of our draft C++ API How might this interoperate with standard C++, graph library proposal? 4[DISTRIBUTION STATEMENT A] This material has been approved for public release GraphBLAS community, C API Overview of our draft C++ API How might this interoperate with standard C++, graph library proposal? 5[DISTRIBUTION STATEMENT A] This material has been approved for public release

Knowledge Graph meet Python Yongpan Sheng 目录 CONTENTS The Pipeline of Knowledge Graph Construction by Data- driven manner Python Tools for Graph Data Management Domain-specific Knowledge Graph Construction relation, object>  Mapping from natural questions to structured queries executable on knowledge graph （机器的潜台词：“我”会推理，so easy ！）。 所以，通俗的来说，在AI system中：要么从原有的知识体系中直接提取信息来使用，要 么进行推理。 将知识融合在机器中，使机器能够利 BigKE将显著提升机器的认知水平。 Preliminaries 本页PPT借鉴于复旦大学肖仰华老师《大数据时代的知识工程与知识管理》 Knowledge Graph – KG引领KE复兴  Knowledge graph is a large-scale semantic network consisting of entities and concepts as well as

top-down task graph What is Task Graph-based Programming System (TGPS) Code 4• TGPS encapsulates function calls and their dependencies in a top-down task graph What is Task Graph-based Programming task graph What is Task Graph-based Programming System (TGPS) Code A B C D B A C D 6• TGPS encapsulates function calls and their dependencies in a top-down task graph What is Task Graph-based precede(task_d); 19 20 sched.schedule(); 21 sched.wait(); B A C D 1. Easy to write and express a task graph 2. Allow to implement irregular parallel decomposition strategies 8Existing TGPSs on Heterogenous

resulting type is the “computational graph”lazy continuations auto k = http::Post(url, body, /* k' */); k.Start(); ● resulting type is the “computational graph” ● the graph is lazy, i.e., nothing has started type is the “computational graph” ● the graph is lazy, i.e., nothing has started when we get it (tradeoff for dynamic allocation) and must be explicitly started ● the graph can be allocated on the stack type is the “computational graph” ● the graph is lazy, i.e., nothing has started when we get it (tradeoff for dynamic allocation) and must be explicitly started ● the graph can be allocated on the stack

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 837 56 Reference for unit ’Graph’ 839 56.1 Used units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . strings, • TCollection (356) to manage collections of objects • TStream (445) classes to support streaming. Furthermore it introduces methods for object persistence, and classes that understand an owner- TFindGlobalComponent is a callback used to find a component in a global scope. It is used when the streaming system needs to find a component which is not part of the component which is currently being streamed

decorator. tornado.web.stream_request_body(cls) Apply to RequestHandler subclasses to enable streaming body support. This decorator implies the following changes: Parameters: HTTPServerRequest.body follow_redirects=None, max_redirects=None, user_agent=None, use_gzip=None, network_interface=None, streaming_callback=None, header_callback=None, prepare_curl_callback=None, proxy_host=None, proxy_port=None request. curl_httpclient only; see not below. streaming_callback (callable [https://docs.python.org/3.5/library/functions.html#callable]) – If set, streaming_callback will be run with each chunk of data

decorator. tornado.web.stream_request_body(cls) Apply to RequestHandler subclasses to enable streaming body support. This decorator implies the following changes: HTTPServerRequest.body is undefined follow_redirects=None, max_redirects=None, user_agent=None, use_gzip=None, network_interface=None, streaming_callback=None, header_callback=None, prepare_curl_callback=None, proxy_host=None, proxy_port=None curl_httpclient only; see not below. streaming_callback (collections.abc.Callable [https://docs.python.org/3.6/library/collections.abc.html#collections.abc.Callab ]) – If set, streaming_callback will be run with

decorator. tornado.web.stream_request_body(cls) Apply to RequestHandler subclasses to enable streaming body support. This decorator implies the following changes: • HTTPServerRequest.body is undefined interface to use for request. curl_httpclient only; see note below. • streaming_callback (collections.abc.Callable) – If set, streaming_callback will be run with each chunk of data as it is received, and HTTPResponse.headers will be empty in the final response. This is most useful in conjunction with streaming_callback, because it’s the only way to get access to header data while the request is in progress