sidereal
Re:Diving Deep on S3 Consistency
on Wednesday April 28, 2021 @10:36AM (#26969850)
The folks involved gave a neat talk about the verification techniques and tools they used as part of AWS Pi Week recently: https://www.twitch.tv/videos/951537246?t=1h10m10s
Re:A Complete Formal Semantics of x86-64 User-Level Instruction Set Ar...
on Tuesday April 23, 2019 @06:38PM (#19733692)
They're specifications in the K Framework, developed by the same group of folks: http://www.kframework.org/index.php/Main_Page
Re:Alloy*: A Higher-Order Relational Constraint Solver
on Wednesday February 27, 2019 @04:13PM (#19266992)
Before learning about Alloy*, you might want to learn about Alloy itself: http://alloy.lcs.mit.edu/alloy/index.html
Hillel Wayne has a great series of blog posts on using Alloy to solve software design problems: https://www.hillelwayne.com/tags/alloy/
Re:EC2 Instances Powered by Arm-Based AWS Graviton Processors
on Monday November 26, 2018 @11:49PM (#18539479)
Looks like A72. Here's the cpuinfo:
processor : 0
BogoMIPS : 166.66
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 cpuid
CPU implementer : 0x41
CPU architecture: 8
CPU variant : 0x0
CPU part : 0xd08
CPU revision : 3
Re:SMT Solving on an iPhone
on Monday November 05, 2018 @07:43PM (#18387372)
I cleaned up that text a little bit -- the 7700K doesn't draw the full 91W TDP when only a single core is loaded, as in this experiment.
Re:Hyperkernel – A push-button approach to building provably correct O...
on Wednesday September 12, 2018 @12:36AM (#17965589)
It’s certainly possible, though it comes with a different set of challenges to software verification. Here’s a recent paper in this direction, proving the correctness of a RISC-V CPU: http://plv.csail.mit.edu/kami/papers/icfp17.pdf
Can you train a neural network using an SMT solver?
Building a Program Synthesizer
How a Diablo expansion led to behind-the-scenes trouble
Re:Learning to Optimize Tensor Programs
on Tuesday May 22, 2018 @06:08PM (#17129810)
Polyhedral optimisation is cool (Facebook has been using it to great effect for ML kernels recently [1]), but it’s not the end of the story. It’s complementary to this paper, which seems to be about learning an effective and transferrable cost model to guide the optimisation process (you could use that learned cost model in a polyhedral optimiser).
Re:Hennessy and Patterson win Turing Award
on Thursday March 22, 2018 @12:29AM (#16645746)
MSR also has Tony Hoare.
Mars Code [pdf]
Re:A study of branch prediction strategies (1981) [pdf]
on Wednesday May 10, 2017 @12:58AM (#14306009)
Today's branch predictors use ideas from machine learning: https://news.ycombinator.com/item?id=12340348
Re:Open-source chip RISC-V to take on closed x86, ARM CPUs
on Sunday May 07, 2017 @12:48AM (#14283916)
Running on a Zedboard is quite well documented; only took me a couple of hours to do it from scratch following their instructions: https://github.com/ucb-bar/fpga-zynq
Intel last year released a preview of their Control-flow Enforcement Technology instructions, which appear to implement these proposed extensions (shadow stack + indirect branch tracking): https://software.intel.com/sites/default/files/managed/4d/2a...