Cs 1: Fill & Download for Free

I’m going to assume that you’d be starting with CS 1. If not, then please let me know.Three of us regularly teach CS 1: myself, Hany Farid, and Devin Balkcom. We all do a very good job. I’m basing that not on my own subjective opinion, but on the course evaluations we get from students. Farid and Balkcom get better course evaluations than I do, and mine are really good. So I don’t think you can go wrong with any of us. By the way, I’ll be teaching CS 1 in Spring 2017, and it will be my 23rd time teaching the introductory computer science course at Dartmouth. I have a little experience with it, and I’ve seen many, many students come in not intending to major in CS but having a life-changing experience in our introductory course. One such student has been retired from Google for 10 years now.Because we’re going to be a little shorthanded next year (among other changes, I’ll be on sabbatical all year), our teaching schedule in 2017–2018 will be a little different. Instead of offering CS 1 in fall, winter, and spring terms, we’re offering it only in fall and spring. Prasad Jayanti will teach it in the fall, and Devin Balkcom in the spring. Prasad has taught CS 1 just once before, but IMHO he is the best teacher at Dartmouth. If he were to offer a course and the course description said “I will read my shopping list,” students would take it. So again, I don’t think you can go wrong with either Jayanti or Balkcom next year.

May I present the Cerebras CS-1. It packs a whopping four hundred THOUSAND cores onto a single processor. Of course that single processor is absolutely massive, containing over a trillion transistors and measuring about eight inches square. This thing is positively ridiculous.And the CPU die, with a baseball for scale:This monster has 18 gigs of on-chip memory…basically L1 cache.It's designed to perform insanely complex machine learning tasks. I have no idea how much one of these behemoths actually costs, but I do know Argonne National Laboratory bought one.Product - Cerebras

This thing.That’s the Cerebras CS-1. It contains this thing, the Wafer Scale Engine:That system takes up only a third of a standard server rack in any modern server farm. Most of the space is for cooling, most of the rest is power supply. With the right cooling infrastructure in the facility, it probably could be redesigned to be half or less of that, but most customers wouldn’t bother.Don’t get me wrong: the compute power contained in little, cheap devices these days is far greater than expensive, beefy servers 15–20 years ago. My last job was drivers and compilers for GPUs in iOS devices, and the last computer I assembled was a Raspberry Pi. Amazing power in tiny packages.However, a CS-1 can do certain computations faster than many of these:HPC Systems“How?” you ask. “There’s so much more silicon in those big clustered supercomputers. They should have far more ability!”This comes to the “strong” part of the question. Any experienced weightlifter can tell you that “strong” that’s isolated to a handful of muscles is just dead weight if something else is the weak link. And for contemporary machine learning problems, the weak link is not the computing power of individual processors, but the transmission of data between them. That’s where the CS-1 is “strong.”Computers are just arrangements of transistors (or past or future devices) organized in various ways, and it’s up to us to figure out paradigms of arranging them so that we can program those computers to do the computations we want them to do, fast. In just 20 years, I’ve worked on FPGAs, GPUs, this, and a bunch of other things. I’m sure there’ll be stuff that makes the CS-1 look ancient before I retire. That’s what keeps life interesting.