Futures in parallel: from tornado.gen import multi async def parallel_fetch(url1, url2): resp1, resp2 = await multi([http_client.fetch(url1), http_client.fetch(url2)]) async def parallel_fetch_many(urls): fetch(url) for url in urls]) # responses is a list of HTTPResponses in the same order async def parallel_fetch_dict(urls): responses = await multi({url: http_client.fetch(url) for url in urls}) # responses In decorated coroutines, it is possible to yield the list or dict directly: @gen.coroutine def parallel_fetch_decorated(url1, url2): resp1, resp2 = yield [http_client.fetch(url1), http_client.fetch(url2)]

code named Phoenix Project, is critical to the future of Parts Unlimited, but the project is massively over budget and very late. The CEO wants Bill to report directly to him and fix the mess in ninety

dicts whose values are Futures, and waits for all of those Futures in parallel: from tornado.gen import multi async def parallel_fetch(url1, url2): resp1, resp2 = await multi([http_client.fetch(url1) async def parallel_fetch_many(urls): responses = await multi ([http_client.fetch(url) for url in urls]) # responses is a list of HTTPResponses in the same order async def parallel_fetch_dict(urls): In decorated coroutines, it is possible to yield the list or dict directly: @gen.coroutine def parallel_fetch_decorated(url1, url2): resp1, resp2 = yield [http_client.fetch(url1),

Models Led To… *A FLOP (floating point operation) is a basic unit of computation used to measure processing power, representing a single arithmetic calculation involving decimal numbers. In AI, total FLOPs on some reasoning tests 3/23: OpenAI releases GPT-4, a multimodal* model capable of processing both text & images 3/23: Google releases Bard, its ChatGPT competitor 11/23: 28 countries designate particularly influential models within the AI/machine learning ecosystem. Epoch maintains a database of 900 AI models released since the 1950s, selecting entries based on criteria such as state-of-the-art

Multicast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 23 Parallel Computing 310 24 Asynchronous Programming 311 24.1 Basic Task operations . . . . . . . . . . of Finalizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 26 Multi-processing and Distributed Computing 329 26.1 Code Availability and Loading Packages . . . . . . . . . . Global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 26.5 Parallel Map and Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 26.6 Remote

Multicast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 23 Parallel Computing 310 24 Asynchronous Programming 311 24.1 Basic Task operations . . . . . . . . . . of Finalizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 26 Multi-processing and Distributed Computing 329 26.1 Code Availability and Loading Packages . . . . . . . . . . Global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 26.5 Parallel Map and Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 26.6 Remote

Multicast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 23 Parallel Computing 310 24 Asynchronous Programming 311 24.1 Basic Task operations . . . . . . . . . . of Finalizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 26 Multi-processing and Distributed Computing 329 26.1 Code Availability and Loading Packages . . . . . . . . . . Global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 26.5 Parallel Map and Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 26.6 Remote

Multicast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 23 Parallel Computing 313 24 Asynchronous Programming 314 24.1 Basic Task operations . . . . . . . . . . of Finalizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 26 Multi-processing and Distributed Computing 333 26.1 Code Availability and Loading Packages . . . . . . . . . . Global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 26.5 Parallel Map and Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340 26.6 Remote

Multicast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 23 Parallel Computing 313 24 Asynchronous Programming 314 24.1 Basic Task operations . . . . . . . . . . of Finalizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 26 Multi-processing and Distributed Computing 332 26.1 Code Availability and Loading Packages . . . . . . . . . . Global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 26.5 Parallel Map and Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 26.6 Remote

Multicast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 23 Parallel Computing 313 24 Asynchronous Programming 314 24.1 Basic Task operations . . . . . . . . . . of Finalizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 26 Multi-processing and Distributed Computing 332 26.1 Code Availability and Loading Packages . . . . . . . . . . Global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 26.5 Parallel Map and Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 26.6 Remote