commit 556f1b3b849c33ba6075fb70a8ad9134e5f6949c
parent 7af0efaa78e15f23cfcd1ae6f95bc8ff82ef6b6e
Author: Andrew Laack <andrew@laack.co>
Date: Tue, 19 May 2026 08:17:09 -0500
Notes on distributed systems in the context of crypto
Diffstat:
7 files changed, 52 insertions(+), 4 deletions(-)
diff --git a/docs/CAPTheorem.md b/docs/CAPTheorem.md
@@ -0,0 +1,29 @@
+# CAP Theorem
+
+**Source:** [https://en.wikipedia.org/wiki/CAP_theorem/](https://en.wikipedia.org/wiki/CAP_theorem/)
+
+**Definition:** The CAP theorem states a distributed data store can only provide at most two of the following characteristics:
+
+1. Consistency
+2. Availability
+3. Partition tolerance
+
+## Consistency
+
+Consistency means every client sees the same data at the same time, regardless of which node it connects to. To achieve this, a write to one node must be instantly replicated across all nodes, and the write is only considered 'successful' once all nodes reflect the write.
+
+## Availability
+
+Every request received by a non-failing node must result in a response.
+
+## Partition Tolerance
+
+The system continues working despite an arbitrary number of messages being dropped between nodes.
+
+## Accepted Tradeoffs
+
+Since networks are generally fallible, partition tolerance is often a necessary tradeoff to accept. As such, one is then left with a choice between consistency and availability.
+
+If consistency is choose, the system will return errors or a time out if information can't be guaranteed to be up to date due to network partitioning.
+
+If availability is chosen the system will try to return the most up to date information, even if it might not be totally up to date.
diff --git a/docs/Cryptocurrency.md b/docs/Cryptocurrency.md
@@ -24,3 +24,5 @@ To achieve distributed consensus it is frequently useful to have a distributed l
- [Depository](Depository.md)
- [Chaumian eCash](ChaumianECash.md)
- [Blockchain](Blockchain.md)
+- [CAP Theorem](CAPTheorem.md)
+- [PACELC](PACELC.md)
diff --git a/docs/FlashCrash.md b/docs/FlashCrash.md
@@ -2,6 +2,4 @@
Superintelligence - Bostrom
-
-
**Definition:** The flash crash occurred in 2010 where two oppositional algorithmic traders began trading back and forth very quickly because their utility function specified they do so, but logically they should not have.
diff --git a/docs/ISA.md b/docs/ISA.md
@@ -2,8 +2,6 @@
Computer Architecture L(2,3)
-
-
**Definition:** The design of the interconnection between hardware and software to create a functional computing system.
This is the agreed upon interface between os/vm/higher level things and lower level [MicroArchitecture](MicroArchitecture.md) This information is necessary to know for the OS developer.
diff --git a/docs/NoteTaking.md b/docs/NoteTaking.md
@@ -4,10 +4,19 @@
I am curious about note taking. There are so many different approaches to taking notes. Of them, are any backed by science? What does modern research tell us about how we should be taking notes, and how does this differ across domains?
+## General Findings
+
+- Spaced repitition is important
+ - More difficult / newer information is repeated more frequently
+
## Links
### Research
+#### 2016
+
+- [The right time to learn: mechanisms and optimization of spaced learning](TheRightTimeToLearn.md)
+
#### 2017
- [An integrative review of the cognitive costs and benefits of note-taking](CognitiveCostsAndBenefitsOfNoteTaking.md)
diff --git a/docs/PACELC.md b/docs/PACELC.md
@@ -0,0 +1,5 @@
+# PACELC
+
+**Source:** [https://en.wikipedia.org/wiki/PACELC_design_principle/](https://en.wikipedia.org/wiki/PACELC_design_principle/)
+
+**Definition:** The PACELC design principle states that in the case of network partitioning (P), one has to choose between availability (A) and consistency (C) (per the [CAP Theorem](CAPTheorem.md)), but else (E), even when the system is running in the absence of partitions, one has to choose between latency (L) and loss of consistency (C).
diff --git a/docs/TheRightTimeToLearn.md b/docs/TheRightTimeToLearn.md
@@ -0,0 +1,7 @@
+# The right time to learn: mechanisms and optimization of spaced learning
+
+**Source:** [https://arxiv.org/abs/1606.08370/](https://arxiv.org/abs/1606.08370/)
+
+## Summary
+
+
