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mlerner

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Graham: Synchronizing Clocks by Leveraging Local Clock Properties (2022) [pdf]

usenix.org
59 points·by mlerner·11 months ago·13 comments

Autothrottle: Resource Management for SLO-Targeted Microservices

usenix.org
22 points·by mlerner·last year·1 comments

Resiliency at Scale: Managing Google's TPUv4 Machine Learning Supercomputer

micahlerner.com
1 points·by mlerner·last year·0 comments

How the anti-cheat is anti-cheating so far

leagueoflegends.com
3 points·by mlerner·2 years ago·0 comments

ServiceRouter: Hyperscale and Minimal Cost Service Mesh at Meta

micahlerner.com
1 points·by mlerner·2 years ago·0 comments

A Cloud-Scale Characterization of Remote Procedure Calls

newsletter.micahlerner.com
2 points·by mlerner·2 years ago·0 comments

A Cloud-Scale Characterization of Google's Remote Procedure Calls

micahlerner.com
1 points·by mlerner·2 years ago·0 comments

Gemini, Amazon's system for fast failure recovery in distributed model training

micahlerner.com
2 points·by mlerner·2 years ago·0 comments

Defcon: Preventing overload with graceful feature degradation (2023)

micahlerner.com
237 points·by mlerner·2 years ago·95 comments

MotherDuck: DuckDB in the Cloud and in the Client [pdf]

cidrdb.org
5 points·by mlerner·2 years ago·0 comments

Gemini: Fast Failure Recovery in Distributed Training with In-Memory Checkpoints

micahlerner.com
3 points·by mlerner·2 years ago·0 comments

Gemini: Fast Failure Recovery in Distributed Training with In-Memory Checkpoints

newsletter.micahlerner.com
4 points·by mlerner·2 years ago·0 comments

XFaaS: Hyperscale and Low Cost Serverless Functions at Meta

newsletter.micahlerner.com
3 points·by mlerner·2 years ago·0 comments

XFaaS: Hyperscale and Low Cost Serverless Functions at Meta

newsletter.micahlerner.com
3 points·by mlerner·2 years ago·1 comments

Blueprint: A Toolchain for Highly-Reconfigurable Microservice Applications

micahlerner.com
2 points·by mlerner·2 years ago·0 comments

Gemini: Fast Failure Recovery in Distributed Training with In-Memory Checkpoints [pdf]

cs.rice.edu
50 points·by mlerner·2 years ago·13 comments

XFaaS: Hyperscale and Low Cost Serverless Functions at Meta [pdf]

cis.upenn.edu
4 points·by mlerner·2 years ago·0 comments

Efficient Memory Management for Large Language Model Serving with PagedAttention

newsletter.micahlerner.com
3 points·by mlerner·2 years ago·0 comments

Efficient Memory Management for Large Language Model Serving with PagedAttention

newsletter.micahlerner.com
1 points·by mlerner·3 years ago·0 comments

Blueprint: A Toolchain for Highly-Reconfigurable Microservice Applications

micahlerner.com
1 points·by mlerner·3 years ago·0 comments

comments

mlerner
·2 years ago·discuss
Author of the paper summary here - my understanding is that XFaaS doesn't run functions that are run in response to user input (e.g. XFaaS does not execute code that fetches and returns data because a user clicked on a button).
mlerner
·3 years ago·discuss
Good catch! Here's the link to the framework: https://gitlab.mpi-sws.org/cld/blueprint/blueprint-compiler.

Also added it to the blog post :)
mlerner
·3 years ago·discuss
The x-axis is size of trade, and the y-axis is % of trades at a specific size. ExRates had _many_ large trades, which shows up as a significantly different distribution than other exchanges like Coinbase/Bitstamp/Kraken (which had many small trades, and a long tail of larger size trades). See slide 42-44 here: https://www.sec.gov/comments/sr-nysearca-2019-01/srnysearca2...
mlerner
·3 years ago·discuss
100% - although this time around there is (in my opinion) _a lot more data_ [1] that regulated markets (like CME bitcoin futures) drive price discovery.

[1] There was data back then too, it just wasn't received.
mlerner
·3 years ago·discuss
The volume we were looking at was on exchanges (not on chain).
mlerner
·3 years ago·discuss
It’s Jekyll - and open source! https://github.com/mlerner/mlerner.github.io
mlerner
·3 years ago·discuss
Neat and funny that they have an uncited figure (the one with the six exchanges with wacky trade size distributions) from research that we did while I was working at Bitwise.

We found 95% of bitcoin trading volume at the time was fake: https://www.wsj.com/articles/most-bitcoin-trading-faked-by-u...
mlerner
·3 years ago·discuss
https://www.micahlerner.com

I write about new and foundational academic CS research - writing is a way for me to learn and share with others along the way.

Some of my most popular writing is:

- FoundationDB: A Distributed Unbundled Transactional Key Value Store (https://news.ycombinator.com/item?id=28740497)

- Monarch: Google’s Planet-Scale In-Memory Time Series Database (https://news.ycombinator.com/item?id=31379383)

- Ray: A Distributed Framework for Emerging AI Applications (https://news.ycombinator.com/item?id=27730807)
mlerner
·3 years ago·discuss
Really neat paper - a while ago I wrote a summary of the system: https://www.micahlerner.com/2021/06/12/foundationdb-a-distri...