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Cache-Oblivious Algorithms and Data Structures - Erik Demaine (One of the earliest papers in cache oblivious data structures and algorithms that introduces the cache oblivious model in detail and examines static and dynamic cache oblivious data structures built between 2000-2003)
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Cache Oblivious B-Trees - Bender, Demaine, Farch-Colton (This paper presents two dynamic search trees attaining near-optimal performance on any hierarchical memory. One of the fundamental papers in the field where both search trees discussed match the optimal search bound of Θ(1+log (B+1)N) memory transfers)
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Cache Oblivious Search Trees via Binary Trees of Small Height - Brodal, Fagerberg, Jacob (The data structure discussed in this paper works on the version of [2] but avoids the use o
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import java.util.function.Consumer; | |
import java.util.function.Function; | |
sealed interface Result<T> { | |
static <TOK> Result<TOK> ok(TOK value) { | |
return new Ok<>(value); | |
} | |
static <TOK> Result<TOK> err(String error) { | |
return new Err<>(error); |
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#r "nuget:Microsoft.ML" | |
#r "nuget:Microsoft.ML.AutoML" | |
#r "nuget:Microsoft.ML.DataView" | |
#r "nuget:Plotly.NET" | |
#r "nuget:FSharp.Data" | |
open Microsoft.ML | |
open Microsoft.ML.Data | |
open Microsoft.ML.Transforms | |
open Microsoft.ML.Trainers |
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package org.example.SingleFileApplication; | |
import lombok.Data; | |
import lombok.RequiredArgsConstructor; | |
import lombok.experimental.Accessors; | |
import org.springframework.beans.factory.annotation.Autowired; | |
import org.springframework.boot.SpringApplication; | |
import org.springframework.boot.autoconfigure.SpringBootApplication; | |
import org.springframework.data.annotation.Id; | |
import org.springframework.data.domain.PageRequest; |
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- name: Import Apple Certificate | |
uses: apple-actions/import-codesign-certs@v1 | |
with: | |
create-keychain: true | |
keychain-password: ${{ secrets.APPSTORE_CERTIFICATE_P12_PASSWORD }} | |
p12-file-base64: ${{ secrets.APPSTORE_CERTIFICATE_P12 }} | |
p12-password: ${{ secrets.APPSTORE_CERTIFICATE_P12_PASSWORD }} | |
- name: Import Mac Installer Certificate | |
uses: apple-actions/import-codesign-certs@v1 |
Being able to SSH directly into a compute job has the advantage of using all remote development tools such as using your IDE's debugger also for GPU jobs (VSCode, PyCharm, ...).
- Slurm: Scheduling system that many HPC clusters use
- Enroot: Container system like Docker for NVIDIA GPUs
General problem:
Here's how I configured a GitHub Action so that a new version issued by GitHub's release interface will build a Dockerfile, tag it with the version number and upload it to Google Artifact Registry.
Before you attempt the steps below, you need the following:
- A GitHub repository that contains a working Dockerfile
- The Google Cloud SDK tool gcloud installed and authenticated
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package s3 | |
import ( | |
"context" | |
"fmt" | |
"github.com/aws/aws-sdk-go-v2/aws" | |
"github.com/aws/aws-sdk-go-v2/config" | |
"github.com/aws/aws-sdk-go-v2/service/s3" | |
"github.com/magiconair/properties/assert" | |
"github.com/testcontainers/testcontainers-go" |
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