changeset 24:876d6c1bc7e6

revision
author Shohei KOKUBO <e105744@ie.u-ryukyu.ac.jp>
date Fri, 19 Feb 2016 05:26:22 +0900
parents f147f579d552
children 7fc1656c2819
files slide/index.html slide/index.md slide/pictures/bitonic.svg slide/pictures/bitonic_all.svg slide/pictures/bitonic_box.svg slide/pictures/bitonic_part.svg slide/pictures/gpu.svg slide/pictures/stream.svg slide/pictures/twice.svg
diffstat 9 files changed, 2611 insertions(+), 7 deletions(-) [+]
line wrap: on
line diff
--- a/slide/index.html	Thu Feb 18 23:01:23 2016 +0900
+++ b/slide/index.html	Fri Feb 19 05:26:22 2016 +0900
@@ -87,7 +87,7 @@
 <!-- === begin markdown block ===
 
       generated by markdown 1.1.1 on Ruby 2.0.0 (2013-02-24) [x86_64-darwin12.3.0]
-                on 2016-02-18 21:56:50 +0900 with Markdown engine kramdown (1.4.0)
+                on 2016-02-19 05:24:33 +0900 with Markdown engine kramdown (1.4.0)
                   using options {}
   -->
 
@@ -119,6 +119,128 @@
 </div>
 <div class='slide '>
 <!-- _S9SLIDE_ -->
+<h1 id="cerium--gpgpu-">Cerium における GPGPU への対応</h1>
+<ul>
+  <li>OpenCL, CUDA を用いて GPGPU に対応している</li>
+  <li>GPGPU ではメモリ空間が異なるためデータ転送が大きなオーバーヘッドになる</li>
+  <li>処理速度を上げるにはデータ転送をオーバーラップする必要がある</li>
+</ul>
+
+<p><img src="./pictures/gpu.svg" alt="GPU" /></p>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="cerium--gpgpu--1">Cerium における GPGPU への対応</h1>
+<ul>
+  <li>Stream に命令を発行することで GPU を制御する</li>
+  <li>Stream は命令が発行された順番通りに実行されることを保証する</li>
+  <li>複数の Stream を用意し、各 Stream に命令を発行することでデータ転送をオーバーラップすることができる</li>
+</ul>
+
+<p><img src="./pictures/stream.svg" alt="stream" /></p>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="bitonic-sort--cerium-">Bitonic Sort を用いた Cerium の評価</h1>
+<ul>
+  <li>Bitonic Sort は並列処理に向いたソートアルゴリズムである</li>
+  <li>最初から最後まで並列度が変わらず、台数による効果が出やすい</li>
+</ul>
+
+<p><img src="./pictures/bitonic.svg" alt="bitonic" /></p>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="bitonic-sort--cerium--1">Bitonic Sort を用いた Cerium の評価</h1>
+<ul>
+  <li>測定環境
+    <ul>
+      <li>Model : MacPro Mid 2010</li>
+      <li>OS : Mac OS X 10.10.5</li>
+      <li>Memory : 16GB</li>
+      <li>CPU : 2 x 6-Core Intel Xeon 2.66GHz</li>
+      <li>GPU : NVIDIA Quadro K5000
+        <ul>
+          <li>Cores : 1536</li>
+          <li>Clock Speed : 706MHz</li>
+          <li>Memory : 4GB GDDR5</li>
+          <li>Memory Bandwidth : 173 GB/s</li>
+        </ul>
+      </li>
+    </ul>
+  </li>
+  <li>要素数:2<sup>20</sup></li>
+</ul>
+
+<table border="1" align="center" width="50%">
+  <tbody>
+    <tr>
+      <td style="text-align: center;">Processor</td>
+      <td style="text-align: center;">Time(ms)</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">1 CPU</td>
+      <td style="text-align: right;">6143</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">2 CPUs</td>
+      <td style="text-align: right;">4633</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">4 CPUs</td>
+      <td style="text-align: right;">2577</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">8 CPUs</td>
+      <td style="text-align: right;">1630</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">12 CPUs</td>
+      <td style="text-align: right;">1318</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">GPU</td>
+      <td style="text-align: right;">155</td>
+    </tr>
+  </tbody>
+</table>
+
+<table width="70%" align="center">
+  <tr>
+    <td><div align="center"><img src="pictures/bitonic_box.svg" width="1024" /></div></td>
+  </tr>
+</table>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="bitonic-sort--cerium--2">Bitonic Sort を用いた Cerium の評価</h1>
+<p>次に要素数を変更して測定を行った。</p>
+
+<table width="70%" align="center">
+  <tr>
+    <td><div align="center"><img src="pictures/bitonic_all.svg" width="1024" /></div></td>
+  </tr>
+  <tr>
+    <td><div align="center"><img src="pictures/bitonic_part.svg" width="1024" /></div></td>
+  </tr>
+</table>
+
+<p>GPU による実行ではデータ転送の時間を考慮する必要がある。</p>
+
+<p>GPGPU は大きなデータに対して有効であることがわかる。</p>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
 <h1 id="cerium-">Cerium の問題点</h1>
 <ul>
   <li>Task 間の依存関係</li>
@@ -405,9 +527,9 @@
 <div class='slide '>
 <!-- _S9SLIDE_ -->
 <h1 id="taskqueue">TaskQueue</h1>
-<p>TaskQueue は Task を管理する。
-すべての Context で共有され並列にアクセスされる。
-CAS 命令を利用してアクセスすることでデータの一貫性を保証する。</p>
+<p>TaskQueue は Task を管理する。</p>
+
+<p>すべての Context で共有され、CAS 命令を利用して変更することで平行にアクセスされてもデータの一貫性を保証する。</p>
 
 <ul lang="C">
   <li>先頭と末尾の要素へのポインタを持った Queue を表す Data Gear</li>
@@ -529,6 +651,291 @@
     } node;
 };
 </code></pre>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="persistent-data-tree-2">Persistent Data Tree</h1>
+<ul>
+  <li>親を取得し、親からの参照を変更して親をスタックに積み直す</li>
+  <li>自分と左右の3点のノードで回転を行うことで平衡にする</li>
+  <li>回転後も条件を満たしているか確認する必要がある</li>
+</ul>
+
+<pre lang="C"><code>// Code Gear
+__code rotateLeft(struct Context* context, struct Node* node, struct Tree* tree, struct Traverse* traverse) {
+    struct Node* tmp = node-&gt;right;
+    struct Node* parent = 0;
+    
+    stack_pop(context-&gt;node_stack, &amp;parent);
+
+    if (parent) {
+        if (node == parent-&gt;left)
+            parent-&gt;left = tmp;
+        else
+            parent-&gt;right = tmp;
+    } else {
+        tree-&gt;root = tmp;
+    }
+
+    stack_push(context-&gt;node_stack, &amp;parent);
+    
+    node-&gt;right = tmp-&gt;left;
+    tmp-&gt;left = node;
+    traverse-&gt;current = tmp;
+    
+    stack_pop(context-&gt;code_stack, &amp;context-&gt;next);
+    goto meta(context, context-&gt;next);
+}
+    
+// Meta Code Gear(stub)
+__code rotateLeft_stub(struct Context* context) {
+    goto rotateLeft(context,
+                    context-&gt;data[Traverse]-&gt;traverse.current,
+                    &amp;context-&gt;data[Tree]-&gt;tree,
+                    &amp;context-&gt;data[Traverse]-&gt;traverse);
+}
+</code></pre>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="worker">Worker</h1>
+<ul>
+  <li>TaskQueue から Task を取得して実行</li>
+  <li>TaskQueue へのアクセスには CAS 命令を用いる</li>
+  <li>Task には実行する Code Gear と実行に必要な Data Gear の key が格納されている</li>
+  <li>Task が完了したら次の Task を取得するために GetQueue に戻ってくる必要がある</li>
+  <li>CAS に失敗したら CAS をやり直すために自分自身に継続する</li>
+</ul>
+
+<pre lang="C"><code>// Task definication
+union Data {
+    // size: 8 byte
+    struct Task {
+        enum Code code;
+        int key;
+    } task;
+}
+</code></pre>
+
+<pre lang="C"><code>// Dequeue
+__code getQueue(struct Context* context, struct Queue* queue, struct Node* node) {
+    if (queue-&gt;first == 0)
+        return;
+
+    struct Element* first = queue-&gt;first;
+    if (__sync_bool_compare_and_swap(&amp;queue-&gt;first, first, first-&gt;next)) {
+        queue-&gt;count--;
+
+        context-&gt;next = GetQueue;
+        stack_push(context-&gt;code_stack, &amp;context-&gt;next);
+
+        context-&gt;next = first-&gt;task-&gt;code;
+        node-&gt;key = first-&gt;task-&gt;key;
+
+        goto meta(context, GetTree);
+    } else {
+        goto meta(context, GetQueue);
+    }
+}
+</code></pre>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="worker-1">Worker</h1>
+<ul>
+  <li>Worker で実行される Code Gear は特別なものではなく、他の Code Gear と同じ記述である
+    <ul>
+      <li>依存関係のない Code Gear はすべて並列に動作させることができることを意味する</li>
+      <li>Gears OS 自体が Code Gear によって構成され、Gears OS の実装自体が Gears Programming の指針となる</li>
+    </ul>
+  </li>
+</ul>
+
+<pre lang="C"><code>// Code Gear
+__code twice(struct Context* context, struct LoopCounter* loopCounter, int index, int alignment, int* array) {
+    int i = loopCounter-&gt;i;
+
+    if (i &lt; alignment) {
+        array[i+index*alignment] = array[i+index*alignment]*2;
+        loopCounter-&gt;i++;
+
+        goto meta(context, Twice);
+    }
+
+    loopCounter-&gt;i = 0;
+
+    stack_pop(context-&gt;code_stack, &amp;context-&gt;next);
+    goto meta(context, context-&gt;next);
+}
+
+// Meta Code Gear(stub)
+__code twice_stub(struct Context* context) {
+    goto twice(context,
+               &amp;context-&gt;data[LoopCounter]-&gt;loopCounter,
+               context-&gt;data[Node]-&gt;node.value-&gt;array.index,
+               context-&gt;data[Node]-&gt;node.value-&gt;array.alignment,
+               context-&gt;data[Node]-&gt;node.value-&gt;array.array);
+}
+</code></pre>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="taskmanager">TaskManager</h1>
+<ul>
+  <li>TaskManager は Task の依存関係の解決を行う</li>
+  <li>Worker の起動・停止も行う</li>
+</ul>
+
+<pre lang="C"><code>// Code Gear
+__code createWorker(struct Context* context, struct LoopCounter* loopCounter, struct Worker* worker) {
+    int i = loopCounter-&gt;i;
+
+    if (i &lt; worker-&gt;num) {
+        struct Context* worker_context = &amp;worker-&gt;contexts[i];
+        worker_context-&gt;next = GetQueue;
+        worker_context-&gt;data[Tree] = context-&gt;data[Tree];
+        worker_context-&gt;data[ActiveQueue] = context-&gt;data[ActiveQueue];
+        pthread_create(&amp;worker_context-&gt;thread, NULL, (void*)&amp;start_code, worker_context);
+        worker_context-&gt;thread_num = i;
+        loopCounter-&gt;i++;
+
+        goto meta(context, CreateWorker);
+    }
+
+    loopCounter-&gt;i = 0;
+    goto meta(context, TaskManager);
+}
+    
+// Meta Code Gear
+__code createWorker_stub(struct Context* context) {
+    goto createWorker(context,
+                      &amp;context-&gt;data[LoopCounter]-&gt;loopCounter,
+                      &amp;context-&gt;data[Worker]-&gt;worker);
+}
+</code></pre>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="gears-os--3">Gears OS の評価</h1>
+<ul>
+  <li>Red-Black Tree アルゴリズムに基づいて非破壊木構造で構築される Persistent Data Tree</li>
+  <li>CAS 命令を用いてアクセスすることで並列に動作させてもデータの一貫性を保証する TaskQueue</li>
+  <li>TaskQueue から Task を取得し実行する Worker</li>
+</ul>
+
+<p>Gears OS を用いて依存関係のない並列処理を実行可能な状態となった</p>
+
+<p>簡単な並列処理の例題を実装し、評価を行う</p>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="twice">Twice</h1>
+<p>依存関係のない簡単な例題として Twice を実装した</p>
+
+<p>Twice は与えられた整数配列を2倍にする例題である</p>
+
+<ul>
+  <li>配列のサイズを元に処理範囲と処理量を決める index, alignment, 配列へのポインタを持つ Data Gear に分割</li>
+  <li>Data Gear を Persistent Data Tree に挿入</li>
+  <li>実行する Code Gear(Twice) と実行に必要な Data Gear の key を持つ Task を生成</li>
+  <li>生成した Task を TaskQueue に挿入</li>
+  <li>Worker の起動</li>
+  <li>Worker が TaskQueue から Task を取得</li>
+  <li>取得した Task を元に必要な Data Gear を Persistent Data Tree から取得</li>
+  <li>Code Gear(Twice) を実行</li>
+</ul>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="result">Result</h1>
+<ul>
+  <li>要素数:2<sup>17</sup> * 1000 elements</li>
+  <li>分割数:640 tasks</li>
+  <li>1 Task 当たりの処理量:2<sup>11</sup> * 100 elements</li>
+</ul>
+
+<table border="1" align="center" width="50%">
+  <tbody>
+    <tr>
+      <td style="text-align: center;">Number of Processors</td>
+      <td style="text-align: center;">Time(ms)</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">1 CPU</td>
+      <td style="text-align: right;">1315</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">2 CPUs</td>
+      <td style="text-align: right;">689</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">4 CPUs</td>
+      <td style="text-align: right;">366</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">8 CPUs</td>
+      <td style="text-align: right;">189</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">12 CPUs</td>
+      <td style="text-align: right;">111</td>
+    </tr>
+  </tbody>
+</table>
+
+<table width="70%" align="center">
+  <tr>
+    <td><div align="center"><img src="pictures/twice.svg" width="1024" /></div></td>
+  </tr>
+</table>
+
+<p>1 CPU と 12 CPU で約11.8倍の速度向上を確認した</p>
+
+<p>十分な台数効果が出ていることがわかる</p>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="section-1">まとめ</h1>
+<ul>
+  <li>Cerium を開発して得られた知見から Code/Data Segment を持つ Gears OS を設計した</li>
+  <li>基本的な機能として Allocator, TaskQueue, Persistent Data Tree, Worker を実装した</li>
+  <li>実装した基本的な機能を組み合わせ Gears OS のプロトタイプを作成し、依存関係のない簡単な並列処理の例題を実装した</li>
+  <li>Gears OS がオーバーヘッドにならず、十分な台数効果が出ることを確認した</li>
+  <li>Gears OS の実装自体が Gears OS を用いて並列処理を記述する際の指針となるように実装した</li>
+</ul>
+
+
+</div>
+<div class='slide '>
+<!-- _S9SLIDE_ -->
+<h1 id="section-2">今後の課題</h1>
+<ul>
+  <li>一般的に並列処理には依存関係が存在する。
+複雑な並列処理を実行できるようにするために依存関係を解決する TaskManager を実装する必要がある</li>
+  <li>GPU など他のプロセッサを演算に利用することができない。
+Code/Data Segment を用いて各プロセッサにのアーキテクチャにマッピングした実行機構を実装する必要がある</li>
+  <li>Data Segment 専用の構文を用意するべきである。
+いまの実装では必要ない Data Segment を持つ場合がある。
+実行可能な Code Segment のリストから推論し必要な Data Segment のみを持つようにする必要がある</li>
+  <li>Data Segment の型情報を検査する機能がない。
+型シグネチャを導入し、プログラムの正しさを保証する型システムを Gears OS 上に実装する必要がある</li>
+</ul>
 <!-- === end markdown block === -->
 </div>
 
--- a/slide/index.md	Thu Feb 18 23:01:23 2016 +0900
+++ b/slide/index.md	Fri Feb 19 05:26:22 2016 +0900
@@ -21,6 +21,94 @@
 
 ![Cerium の構成](./pictures/createTask.svg)
 
+# Cerium における GPGPU への対応
+* OpenCL, CUDA を用いて GPGPU に対応している
+* GPGPU ではメモリ空間が異なるためデータ転送が大きなオーバーヘッドになる
+* 処理速度を上げるにはデータ転送をオーバーラップする必要がある
+
+![GPU](./pictures/gpu.svg)
+
+# Cerium における GPGPU への対応
+* Stream に命令を発行することで GPU を制御する
+* Stream は命令が発行された順番通りに実行されることを保証する
+* 複数の Stream を用意し、各 Stream に命令を発行することでデータ転送をオーバーラップすることができる
+
+![stream](./pictures/stream.svg)
+
+# Bitonic Sort を用いた Cerium の評価
+* Bitonic Sort は並列処理に向いたソートアルゴリズムである
+* 最初から最後まで並列度が変わらず、台数による効果が出やすい
+
+![bitonic](./pictures/bitonic.svg)
+
+# Bitonic Sort を用いた Cerium の評価
+* 測定環境
+  * Model : MacPro Mid 2010
+  * OS : Mac OS X 10.10.5
+  * Memory : 16GB
+  * CPU : 2 x 6-Core Intel Xeon 2.66GHz
+  * GPU : NVIDIA Quadro K5000
+    * Cores : 1536
+    * Clock Speed : 706MHz
+    * Memory : 4GB GDDR5
+    * Memory Bandwidth : 173 GB/s
+* 要素数:2<sup>20</sup>
+
+<table  border="1" align='center' width='50%'>
+  <tbody>
+    <tr>
+      <td style="text-align: center;">Processor</td>
+      <td style="text-align: center;">Time(ms)</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">1 CPU</td>
+      <td style="text-align: right;">6143</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">2 CPUs</td>
+      <td style="text-align: right;">4633</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">4 CPUs</td>
+      <td style="text-align: right;">2577</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">8 CPUs</td>
+      <td style="text-align: right;">1630</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">12 CPUs</td>
+      <td style="text-align: right;">1318</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">GPU</td>
+      <td style="text-align: right;">155</td>
+    </tr>
+  </tbody>
+</table>
+
+<table width="70%" align="center">
+  <tr>
+    <td><div align="center"><img src="pictures/bitonic_box.svg" width="1024"></div></td>
+  </tr>
+</table>
+
+# Bitonic Sort を用いた Cerium の評価
+次に要素数を変更して測定を行った。
+
+<table width="70%" align="center">
+  <tr>
+    <td><div align="center"><img src="pictures/bitonic_all.svg" width="1024"></div></td>
+  </tr>
+  <tr>
+    <td><div align="center"><img src="pictures/bitonic_part.svg" width="1024"></div></td>
+  </tr>
+</table>
+
+GPU による実行ではデータ転送の時間を考慮する必要がある。
+
+GPGPU は大きなデータに対して有効であることがわかる。
+
 # Cerium の問題点
 * Task 間の依存関係
 
@@ -238,8 +326,8 @@
 
 # TaskQueue
 TaskQueue は Task を管理する。
-すべての Context で共有され並列にアクセスされる。
-CAS 命令を利用してアクセスすることでデータの一貫性を保証する。
+
+すべての Context で共有され、CAS 命令を利用して変更することで平行にアクセスされてもデータの一貫性を保証する。
 
 * 先頭と末尾の要素へのポインタを持った Queue を表す Data Gear
 * Task と次の要素へのポインタを持った Element を表す Data Gear
@@ -346,4 +434,234 @@
 ```
 
 # Persistent Data Tree
-* 自分、親、
\ No newline at end of file
+* 親を取得し、親からの参照を変更して親をスタックに積み直す
+* 自分と左右の3点のノードで回転を行うことで平衡にする
+* 回転後も条件を満たしているか確認する必要がある
+
+```C
+// Code Gear
+__code rotateLeft(struct Context* context, struct Node* node, struct Tree* tree, struct Traverse* traverse) {
+    struct Node* tmp = node->right;
+    struct Node* parent = 0;
+    
+    stack_pop(context->node_stack, &parent);
+
+    if (parent) {
+        if (node == parent->left)
+            parent->left = tmp;
+        else
+            parent->right = tmp;
+    } else {
+        tree->root = tmp;
+    }
+
+    stack_push(context->node_stack, &parent);
+    
+    node->right = tmp->left;
+    tmp->left = node;
+    traverse->current = tmp;
+    
+    stack_pop(context->code_stack, &context->next);
+    goto meta(context, context->next);
+}
+    
+// Meta Code Gear(stub)
+__code rotateLeft_stub(struct Context* context) {
+    goto rotateLeft(context,
+                    context->data[Traverse]->traverse.current,
+                    &context->data[Tree]->tree,
+                    &context->data[Traverse]->traverse);
+}
+```
+
+# Worker
+* TaskQueue から Task を取得して実行
+* TaskQueue へのアクセスには CAS 命令を用いる
+* Task には実行する Code Gear と実行に必要な Data Gear の key が格納されている
+* Task が完了したら次の Task を取得するために GetQueue に戻ってくる必要がある
+* CAS に失敗したら CAS をやり直すために自分自身に継続する
+
+```C
+// Task definication
+union Data {
+    // size: 8 byte
+    struct Task {
+        enum Code code;
+        int key;
+    } task;
+}
+```
+
+```C
+// Dequeue
+__code getQueue(struct Context* context, struct Queue* queue, struct Node* node) {
+    if (queue->first == 0)
+        return;
+
+    struct Element* first = queue->first;
+    if (__sync_bool_compare_and_swap(&queue->first, first, first->next)) {
+        queue->count--;
+
+        context->next = GetQueue;
+        stack_push(context->code_stack, &context->next);
+
+        context->next = first->task->code;
+        node->key = first->task->key;
+
+        goto meta(context, GetTree);
+    } else {
+        goto meta(context, GetQueue);
+    }
+}
+```
+
+# Worker
+* Worker で実行される Code Gear は特別なものではなく、他の Code Gear と同じ記述である
+  * 依存関係のない Code Gear はすべて並列に動作させることができることを意味する
+  * Gears OS 自体が Code Gear によって構成され、Gears OS の実装自体が Gears Programming の指針となる
+
+```C
+// Code Gear
+__code twice(struct Context* context, struct LoopCounter* loopCounter, int index, int alignment, int* array) {
+    int i = loopCounter->i;
+
+    if (i < alignment) {
+        array[i+index*alignment] = array[i+index*alignment]*2;
+        loopCounter->i++;
+
+        goto meta(context, Twice);
+    }
+
+    loopCounter->i = 0;
+
+    stack_pop(context->code_stack, &context->next);
+    goto meta(context, context->next);
+}
+
+// Meta Code Gear(stub)
+__code twice_stub(struct Context* context) {
+    goto twice(context,
+               &context->data[LoopCounter]->loopCounter,
+               context->data[Node]->node.value->array.index,
+               context->data[Node]->node.value->array.alignment,
+               context->data[Node]->node.value->array.array);
+}
+```
+
+# TaskManager
+* TaskManager は Task の依存関係の解決を行う
+* Worker の起動・停止も行う
+
+```C
+// Code Gear
+__code createWorker(struct Context* context, struct LoopCounter* loopCounter, struct Worker* worker) {
+    int i = loopCounter->i;
+
+    if (i < worker->num) {
+        struct Context* worker_context = &worker->contexts[i];
+        worker_context->next = GetQueue;
+        worker_context->data[Tree] = context->data[Tree];
+        worker_context->data[ActiveQueue] = context->data[ActiveQueue];
+        pthread_create(&worker_context->thread, NULL, (void*)&start_code, worker_context);
+        worker_context->thread_num = i;
+        loopCounter->i++;
+
+        goto meta(context, CreateWorker);
+    }
+
+    loopCounter->i = 0;
+    goto meta(context, TaskManager);
+}
+    
+// Meta Code Gear
+__code createWorker_stub(struct Context* context) {
+    goto createWorker(context,
+                      &context->data[LoopCounter]->loopCounter,
+                      &context->data[Worker]->worker);
+}
+```
+
+# Gears OS の評価
+* Red-Black Tree アルゴリズムに基づいて非破壊木構造で構築される Persistent Data Tree
+* CAS 命令を用いてアクセスすることで並列に動作させてもデータの一貫性を保証する TaskQueue
+* TaskQueue から Task を取得し実行する Worker
+
+Gears OS を用いて依存関係のない並列処理を実行可能な状態となった
+
+簡単な並列処理の例題を実装し、評価を行う
+
+# Twice
+依存関係のない簡単な例題として Twice を実装した
+
+Twice は与えられた整数配列を2倍にする例題である
+
+* 配列のサイズを元に処理範囲と処理量を決める index, alignment, 配列へのポインタを持つ Data Gear に分割
+* Data Gear を Persistent Data Tree に挿入
+* 実行する Code Gear(Twice) と実行に必要な Data Gear の key を持つ Task を生成
+* 生成した Task を TaskQueue に挿入
+* Worker の起動
+* Worker が TaskQueue から Task を取得
+* 取得した Task を元に必要な Data Gear を Persistent Data Tree から取得
+* Code Gear(Twice) を実行
+
+# Result
+* 要素数:2<sup>17</sup> * 1000 elements
+* 分割数:640 tasks
+* 1 Task 当たりの処理量:2<sup>11</sup> * 100 elements
+
+<table  border="1" align='center' width='50%'>
+  <tbody>
+    <tr>
+      <td style="text-align: center;">Number of Processors</td>
+      <td style="text-align: center;">Time(ms)</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">1 CPU</td>
+      <td style="text-align: right;">1315</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">2 CPUs</td>
+      <td style="text-align: right;">689</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">4 CPUs</td>
+      <td style="text-align: right;">366</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">8 CPUs</td>
+      <td style="text-align: right;">189</td>
+    </tr>
+    <tr>
+      <td style="text-align: center;">12 CPUs</td>
+      <td style="text-align: right;">111</td>
+    </tr>
+  </tbody>
+</table>
+
+<table width="70%" align="center">
+  <tr>
+    <td><div align="center"><img src="pictures/twice.svg" width="1024"></div></td>
+  </tr>
+</table>
+
+1 CPU と 12 CPU で約11.8倍の速度向上を確認した
+
+十分な台数効果が出ていることがわかる
+
+# まとめ
+* Cerium を開発して得られた知見から Code/Data Segment を持つ Gears OS を設計した
+* 基本的な機能として Allocator, TaskQueue, Persistent Data Tree, Worker を実装した
+* 実装した基本的な機能を組み合わせ Gears OS のプロトタイプを作成し、依存関係のない簡単な並列処理の例題を実装した
+* Gears OS がオーバーヘッドにならず、十分な台数効果が出ることを確認した
+* Gears OS の実装自体が Gears OS を用いて並列処理を記述する際の指針となるように実装した
+
+# 今後の課題
+* 一般的に並列処理には依存関係が存在する。
+複雑な並列処理を実行できるようにするために依存関係を解決する TaskManager を実装する必要がある
+* GPU など他のプロセッサを演算に利用することができない。
+Code/Data Segment を用いて各プロセッサにのアーキテクチャにマッピングした実行機構を実装する必要がある
+* Data Segment 専用の構文を用意するべきである。
+いまの実装では必要ない Data Segment を持つ場合がある。
+実行可能な Code Segment のリストから推論し必要な Data Segment のみを持つようにする必要がある
+* Data Segment の型情報を検査する機能がない。
+型シグネチャを導入し、プログラムの正しさを保証する型システムを Gears OS 上に実装する必要がある
\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
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