See also notes on:

  • Computer Architecture
  • Operating Systems

Memory Models

What’s the point? There is a mismatch between both

  1. High level languages (C/Java/Ocaml) and assembly
  2. Assembly and CPU internals

This mismatch is good. The mismatch is abstraction. It gives simpler programming models to users. It allows certain optimizations to happen that the programmer wouldn’t have thought of. The programmer doesn’t necessarily want to say exactly which transistor is flipped at exactly what moment. There is a higher level goal of solving a matrix problem, or writing a record to memory, or swapping two variables.

In a non threaded code we actually don’t care if the follwing two instruction are reordered. store 1 in a store 42 in b

And if there is some reason why it would be faster to do so, sure, go for it compiler. So the program order is not really the execution order insisted upon by single threaded code. It doesn’t however alllow rearrangement of

print(“hello”) print(“world”)

Perhaps however, we are relying on this order to implement some shared primitive.

When you compile, there are intermediate states of the target that don’t really correspond to anything. Depending on the conceptual distance between the source and target, these states may be short. If you point at some particular section of assembly, you probably say, ah yes, it is in the middle of trying to achieve this statement in the source. “In the middle” is not a very precise statement though.

Some things that seem intuitively atomic at the source are not in the target. One statement may become multiple, that a concurrent processor could screw with.

Memory Order vs Program Order

Memory order Program

Program order is the code order in the source. This is vaguely evokes the image of a linear sequence of statements. This is not really what high level languages look like. They have compound statements and expressions, and control flow. The syntax commonly is thought to be tree-like. Is a statement in a loop “before” another? They are executed multiple times, so sure the action during the execution of the loop comes before another, but syntactic statements in the loop correspond to a whole family of actions across all executions of the loop.

Even in single threaded code, execution does not need to follow program order. Non interfering stores and loads are allowed to be slid over each other. Common subexpression elimination means computations may not even happen when they do in the program. Function calls and system calls are probably required to stay in the same order as the source.

We could describe some realatively concrete concurrent machine, with some layer of caching. Does the variable “a” in code exist in the execution of this machine. We are already used to “a” depending on time. But it also not depends on location. It is conceivable that Thread 1, Thread 2, Cache 1 have different opinions on what “a” at the “same” time. Their clocks stay synchronized? Quite an assumption.

Consistency vs Coherence

Sequential Consistency (SC)

Total Store Order (TSO)

Relaxed Memory Models

Fence Instructions

The fact that assembly instructions are a linear stream is a bit silly. This is not a great match for how the unstructions are executed. They are executed out of order and pipelined. The processor can see local data dependncies and creates stalls for those. But nonlocal dependencies on simulatnesous memory access can’t be automatically seen? So you can sort of demarcate regions of the linear stream tht can’t be moved past each other.

VLIW processors for example can schemes for having streams of concurrent operations.


C concurrency model on x86 for dummies



Arguably these are garbage collection topics?


Read Copy Update

Kind of a functional approach. Make new nodes, keeep old ones around.


Very similar/identical to RCU? Maintain global epoch counter. Data is more read only than reference counting

Hazard Pointers

Lock free cliff click a lock free hash table Compare and swap operations. lock -free - at least one thread is making progress. Consider schedulaers. Consider threads getting killed CAS loop wait free - all threadsmaking progress obstruction free ABA problem Lock-free linked list / stack. Pointers with counters so that you can detect reuse of freed memory


Atomics are a way to mark thread shared variables in a sense. Many instances of variables in high level code are a delusion. Assignment to them is not supposed to be a real observable effect. Threads have a “debugger” view into your code.

Maybe a better starting point (or even equally valid as assuming literality of code) is every statement can be reordered. Ok then this isn’t quite true. There are certain restrictions.

a = 2; x = 3; a = 3; These assignments aren’t real. Loop reordering

Data Race Freedom

Memory Barriers: a Hardware View for Software Hackers Memory access ordering an introduction string vs weak memory models - programming languages need to be as weak as the weakest hardware they target, or else they can’t generate optimal code. Interesting.

C assignment is not imperative assignment really. The resulting code is not required to have an instruction that corresponds to it. It is more like a functional binding. So then relying on it for some concurrent construct (and concurrency is stateful/imperative?) is nonsensical

Caches. One model of the problem is to imagine your program runs literally, but then randomly flushes a store cache out to main memory.

Binary Translators for Weak Memory Model Architectures

Data Race Freedom


Concurrency Mutex Lock Concurrent hash table barriers

  • - bartosz on c++11 concurrency

pthread vs std::thread Arc in rust condition variables



C++/Java/Ocaml memory models

  • - interesting thesis too
  • hans boehm link farm - “impossible as a library”
  • - mathematizzing C++ memory model, kodkod, isabelle

Various kinds of relations.

futex - fast userspace mutex

MPI Cilk OpenMP

rust model checker actor system thing

Leslie lamport

  • Lindsey kuper has a dist sys course It’s probably pretty good

Lecture 1. several node,s connected by network, characterized by partial failure cloud vs hpc cloud treat failure as expected and work around it “Eveerything fails all tyhe timne” - werner vogels hpc- partial is total failure. checkpointing

M1 -> M2 x? Posslbe problems:

  1. lost request
  2. request from M1 is slow
  3. M2 crashes
  4. M2 slow to respond
  5. seponse is slow
  6. response could get lost
  7. corrupt - byzantine faults.

important: send request to another node and don’t receive a response, it is impossible for you to know why

How do real systems cope? Timeout - wait a certain amount of time then assume failure - imperfect solutuojn

max delay d. max process time r. cn’t really do this asynchronous network - no max Palvaro - partiasl failure + unbounded latency

  • - dedalus - datalog in time and space. bloom blazes, data lineage multiple proofs are fault tolerant. lineage. Why did happen: produce explanation / proof. Cegis? concolic kind of? observability.



  • kyle kingsbury

  • chaos engineering - nora jones netflix


Lecture 2 - kuper

clocks. scheduling. intervals in time time of day clocks, monotonic clocks NTP network time protocl. not so good for measuring inervals. can jump forward or backward cloudflare leap second bug monotonic - only goes forward

import time time.monotonic() . not comparable between machines

logical clocks only measuring order of events. A can cause B, not vie versa lamport diagrams/ spacetime daigrams

network models synhcrnous network is one where exists an n such no message takes longer than n asynchrnous - one where the is no n such that no message takes longer than n units “partially synchrnous” n exists but you don’t know what it is

happens before - on same process. if a is send,, and b is receive, then a is before c, trasntivity concurrent - not ordered

state -

mate soos talking about adding mpi z3 had mpi but was disabled. armin biere talking about pthreads - pligenling uses pthreads