This is an automated email from the ASF dual-hosted git repository.
tqchen pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-tvm-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 6f2222a Build at Sun Mar 29 11:17:22 PDT 2020
6f2222a is described below
commit 6f2222a9c53d34e3378ba90f1132299399e89701
Author: tqchen <[email protected]>
AuthorDate: Sun Mar 29 11:17:22 2020 -0700
Build at Sun Mar 29 11:17:22 PDT 2020
---
...PUs-to-TVM-Stack-and-NNVM-Compiler-with-ROCm.html | 16 ++++++++--------
about.html | 12 +++++++-----
atom.xml | 18 +++++++++---------
index.html | 2 +-
rss.xml | 20 ++++++++++----------
vta.html | 10 ++++++----
6 files changed, 41 insertions(+), 37 deletions(-)
diff --git
a/2017/10/30/Bringing-AMDGPUs-to-TVM-Stack-and-NNVM-Compiler-with-ROCm.html
b/2017/10/30/Bringing-AMDGPUs-to-TVM-Stack-and-NNVM-Compiler-with-ROCm.html
index b97a4b1..7f90255 100644
--- a/2017/10/30/Bringing-AMDGPUs-to-TVM-Stack-and-NNVM-Compiler-with-ROCm.html
+++ b/2017/10/30/Bringing-AMDGPUs-to-TVM-Stack-and-NNVM-Compiler-with-ROCm.html
@@ -262,13 +262,13 @@ We are starting to look at performance optimization and
we expect more improveme
<p>You should see something like this:</p>
<figure class="highlight"><pre><code class="language-llvm"
data-lang="llvm"><span class="c1">; ModuleID = 'myadd__kernel0'</span>
-<span class="err">sour</span><span class="k">c</span><span
class="err">e_filename</span> <span class="p">=</span> <span
class="s">"myadd__kernel0"</span>
+<span class="err">source_filename</span> <span class="p">=</span> <span
class="s">"myadd__kernel0"</span>
<span class="k">target</span> <span class="k">datalayout</span> <span
class="p">=</span> <span
class="s">"e-p:32:32-p1:64:64-p2:64:64-p3:32:32-p4:64:64-p5:32:32-i64:64-v16:16-v24:32-v32:32-v48:64-v96:128-v192:256-v256:256-v512:512-v1024:1024-v2048:2048-n32:64"</span>
<span class="k">target</span> <span class="k">triple</span> <span
class="p">=</span> <span class="s">"amdgcn-amd-amdhsa-hcc"</span>
<span class="c1">; Function Attrs: nounwind</span>
-<span class="k">define</span> <span class="k">dllexport</span> <span
class="err">amdgpu_ker</span><span class="k">ne</span><span
class="err">l</span> <span class="kt">void</span> <span
class="vg">@myadd__kernel0</span><span class="p">(</span><span
class="kt">float</span> <span class="k">add</span><span
class="err">rspa</span><span class="k">c</span><span class="err">e</span><span
class="p">(</span><span class="m">1</span><span class="p">)*</span> <span
class="k">noalias</span> <span clas [...]
+<span class="k">define</span> <span class="k">dllexport</span> <span
class="err">amdgpu_kernel</span> <span class="kt">void</span> <span
class="vg">@myadd__kernel0</span><span class="p">(</span><span
class="kt">float</span> <span class="k">addrspace</span><span
class="p">(</span><span class="m">1</span><span class="p">)*</span> <span
class="k">noalias</span> <span class="k">nocapture</span><span
class="p">,</span> <span class="kt">float</span> <span
class="k">addrspace</span><span class= [...]
<span class="nl">entry:</span>
<span class="nv">%4</span> <span class="p">=</span> <span
class="k">tail</span> <span class="k">call</span> <span class="kt">i32</span>
<span class="vg">@llvm.amdgcn.workgroup.id.x</span><span class="p">()</span>
<span class="nv">%5</span> <span class="p">=</span> <span
class="k">tail</span> <span class="k">call</span> <span class="kt">i32</span>
<span class="vg">@llvm.amdgcn.workitem.id.x</span><span class="p">()</span>
@@ -288,14 +288,14 @@ We are starting to look at performance optimization and
we expect more improveme
<span class="nv">%10</span> <span class="p">=</span> <span
class="k">add</span> <span class="k">nsw</span> <span class="kt">i32</span>
<span class="nv">%.pre-phi</span><span class="p">,</span> <span
class="nv">%5</span>
<span class="nv">%11</span> <span class="p">=</span> <span
class="k">add</span> <span class="k">nsw</span> <span class="kt">i32</span>
<span class="nv">%.pre-phi</span><span class="p">,</span> <span
class="nv">%5</span>
<span class="nv">%12</span> <span class="p">=</span> <span
class="k">sext</span> <span class="kt">i32</span> <span class="nv">%11</span>
<span class="k">to</span> <span class="kt">i64</span>
- <span class="nv">%13</span> <span class="p">=</span> <span
class="k">getelementptr</span> <span class="k">inbounds</span> <span
class="kt">float</span><span class="p">,</span> <span class="kt">float</span>
<span class="k">add</span><span class="err">rspa</span><span
class="k">c</span><span class="err">e</span><span class="p">(</span><span
class="m">1</span><span class="p">)*</span> <span class="nv">%2</span><span
class="p">,</span> <span class="kt">i64</span> <span class="nv">%12</span>
- <span class="nv">%14</span> <span class="p">=</span> <span
class="k">load</span> <span class="kt">float</span><span class="p">,</span>
<span class="kt">float</span> <span class="k">add</span><span
class="err">rspa</span><span class="k">c</span><span class="err">e</span><span
class="p">(</span><span class="m">1</span><span class="p">)*</span> <span
class="nv">%13</span><span class="p">,</span> <span class="k">align</span>
<span class="m">4</span><span class="p">,</span> <span class="nv" [...]
- <span class="nv">%15</span> <span class="p">=</span> <span
class="k">getelementptr</span> <span class="k">inbounds</span> <span
class="kt">float</span><span class="p">,</span> <span class="kt">float</span>
<span class="k">add</span><span class="err">rspa</span><span
class="k">c</span><span class="err">e</span><span class="p">(</span><span
class="m">1</span><span class="p">)*</span> <span class="nv">%1</span><span
class="p">,</span> <span class="kt">i64</span> <span class="nv">%12</span>
- <span class="nv">%16</span> <span class="p">=</span> <span
class="k">load</span> <span class="kt">float</span><span class="p">,</span>
<span class="kt">float</span> <span class="k">add</span><span
class="err">rspa</span><span class="k">c</span><span class="err">e</span><span
class="p">(</span><span class="m">1</span><span class="p">)*</span> <span
class="nv">%15</span><span class="p">,</span> <span class="k">align</span>
<span class="m">4</span><span class="p">,</span> <span class="nv" [...]
+ <span class="nv">%13</span> <span class="p">=</span> <span
class="k">getelementptr</span> <span class="k">inbounds</span> <span
class="kt">float</span><span class="p">,</span> <span class="kt">float</span>
<span class="k">addrspace</span><span class="p">(</span><span
class="m">1</span><span class="p">)*</span> <span class="nv">%2</span><span
class="p">,</span> <span class="kt">i64</span> <span class="nv">%12</span>
+ <span class="nv">%14</span> <span class="p">=</span> <span
class="k">load</span> <span class="kt">float</span><span class="p">,</span>
<span class="kt">float</span> <span class="k">addrspace</span><span
class="p">(</span><span class="m">1</span><span class="p">)*</span> <span
class="nv">%13</span><span class="p">,</span> <span class="k">align</span>
<span class="m">4</span><span class="p">,</span> <span class="nv">!tbaa</span>
<span class="nv">!2</span>
+ <span class="nv">%15</span> <span class="p">=</span> <span
class="k">getelementptr</span> <span class="k">inbounds</span> <span
class="kt">float</span><span class="p">,</span> <span class="kt">float</span>
<span class="k">addrspace</span><span class="p">(</span><span
class="m">1</span><span class="p">)*</span> <span class="nv">%1</span><span
class="p">,</span> <span class="kt">i64</span> <span class="nv">%12</span>
+ <span class="nv">%16</span> <span class="p">=</span> <span
class="k">load</span> <span class="kt">float</span><span class="p">,</span>
<span class="kt">float</span> <span class="k">addrspace</span><span
class="p">(</span><span class="m">1</span><span class="p">)*</span> <span
class="nv">%15</span><span class="p">,</span> <span class="k">align</span>
<span class="m">4</span><span class="p">,</span> <span class="nv">!tbaa</span>
<span class="nv">!6</span>
<span class="nv">%17</span> <span class="p">=</span> <span
class="k">fadd</span> <span class="kt">float</span> <span
class="nv">%14</span><span class="p">,</span> <span class="nv">%16</span>
<span class="nv">%18</span> <span class="p">=</span> <span
class="k">sext</span> <span class="kt">i32</span> <span class="nv">%10</span>
<span class="k">to</span> <span class="kt">i64</span>
- <span class="nv">%19</span> <span class="p">=</span> <span
class="k">getelementptr</span> <span class="k">inbounds</span> <span
class="kt">float</span><span class="p">,</span> <span class="kt">float</span>
<span class="k">add</span><span class="err">rspa</span><span
class="k">c</span><span class="err">e</span><span class="p">(</span><span
class="m">1</span><span class="p">)*</span> <span class="nv">%0</span><span
class="p">,</span> <span class="kt">i64</span> <span class="nv">%18</span>
- <span class="k">store</span> <span class="kt">float</span> <span
class="nv">%17</span><span class="p">,</span> <span class="kt">float</span>
<span class="k">add</span><span class="err">rspa</span><span
class="k">c</span><span class="err">e</span><span class="p">(</span><span
class="m">1</span><span class="p">)*</span> <span class="nv">%19</span><span
class="p">,</span> <span class="k">align</span> <span class="m">4</span><span
class="p">,</span> <span class="nv">!tbaa</span> <span clas [...]
+ <span class="nv">%19</span> <span class="p">=</span> <span
class="k">getelementptr</span> <span class="k">inbounds</span> <span
class="kt">float</span><span class="p">,</span> <span class="kt">float</span>
<span class="k">addrspace</span><span class="p">(</span><span
class="m">1</span><span class="p">)*</span> <span class="nv">%0</span><span
class="p">,</span> <span class="kt">i64</span> <span class="nv">%18</span>
+ <span class="k">store</span> <span class="kt">float</span> <span
class="nv">%17</span><span class="p">,</span> <span class="kt">float</span>
<span class="k">addrspace</span><span class="p">(</span><span
class="m">1</span><span class="p">)*</span> <span class="nv">%19</span><span
class="p">,</span> <span class="k">align</span> <span class="m">4</span><span
class="p">,</span> <span class="nv">!tbaa</span> <span class="nv">!9</span>
<span class="k">br</span> <span class="kt">label</span> <span
class="nv">%if_end</span>
diff --git a/about.html b/about.html
index 45da8ac..9760388 100644
--- a/about.html
+++ b/about.html
@@ -149,9 +149,9 @@
<div class="row">
<div class="span14">
-<h1 id="about-tvm">About TVM</h1>
+<h1 id="about-apache-incubating-tvm">About Apache (incubating) TVM</h1>
-<p>TVM is an open deep learning compiler stack for CPUs, GPUs, and specialized
accelerators. It aims to close the gap between the productivity-focused deep
learning frameworks,
+<p>Apache(incubating) TVM is an open deep learning compiler stack for CPUs,
GPUs, and specialized accelerators. It aims to close the gap between the
productivity-focused deep learning frameworks,
and the performance- or efficiency-oriented hardware backends. TVM provides
the following main features:</p>
<ul>
@@ -160,9 +160,11 @@ and the performance- or efficiency-oriented hardware
backends. TVM provides the
on more backend with better performance.</li>
</ul>
-<p>TVM stack began as a research project at the <a
href="https://sampl.cs.washington.edu/";>SAMPL group</a> of
-Paul G. Allen School of Computer Science & Engineering, University of
Washington. The project is now driven by an open source community involving
multiple industry and academic institutions.
-The project adopts <a
href="https://docs.tvm.ai/contribute/community.html";>Apache-style merit based
governace model</a>.</p>
+<p>TVM began as a research project at the <a
href="https://sampl.cs.washington.edu/";>SAMPL group</a> of
+Paul G. Allen School of Computer Science & Engineering, University of
Washington.
+The project is now an effort undergoing incubation at The Apache Software
Foundation (ASF),
+driven by an open source community involving multiple industry and academic
institutions
+under the Apache way.</p>
<p>TVM provides two level optimizations show in the following figure.
Computational graph optimization to perform tasks such as high-level operator
fusion, layout transformation, and memory management.
diff --git a/atom.xml b/atom.xml
index 6cb7862..66849b4 100644
--- a/atom.xml
+++ b/atom.xml
@@ -4,7 +4,7 @@
<title>TVM</title>
<link href="https://tvm.apache.org"; rel="self"/>
<link href="https://tvm.apache.org"/>
- <updated>2020-03-22T15:42:25-07:00</updated>
+ <updated>2020-03-29T11:17:22-07:00</updated>
<id>https://tvm.apache.org</id>
<author>
<name></name>
@@ -2696,13 +2696,13 @@ We are starting to look at performance optimization and
we expect more improveme
<p>You should see something like this:</p>
<figure class="highlight"><pre><code
class="language-llvm" data-lang="llvm"><span
class="c1">; ModuleID = 'myadd__kernel0'</span>
-<span class="err">sour</span><span
class="k">c</span><span
class="err">e_filename</span> <span
class="p">=</span> <span
class="s">"myadd__kernel0"</span>
+<span class="err">source_filename</span> <span
class="p">=</span> <span
class="s">"myadd__kernel0"</span>
<span class="k">target</span> <span
class="k">datalayout</span> <span
class="p">=</span> <span
class="s">"e-p:32:32-p1:64:64-p2:64:64-p3:32:32-p4:64:64-p5:32:32-i64:64-v16:16-v24:32-v32:32-v48:64-v96:128-v192:256-v256:256-v512:512-v1024:1024-v2048:2048-n32:64"</span>
<span class="k">target</span> <span
class="k">triple</span> <span
class="p">=</span> <span
class="s">"amdgcn-amd-amdhsa-hcc"</span>
<span class="c1">; Function Attrs: nounwind</span>
-<span class="k">define</span> <span
class="k">dllexport</span> <span
class="err">amdgpu_ker</span><span
class="k">ne</span><span
class="err">l</span> <span
class="kt">void</span> <span
class="vg">@myadd__kernel0</span><span
class="p">(</span><span
class="kt">float</span> <span class="k [...]
+<span class="k">define</span> <span
class="k">dllexport</span> <span
class="err">amdgpu_kernel</span> <span
class="kt">void</span> <span
class="vg">@myadd__kernel0</span><span
class="p">(</span><span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span class [...]
<span class="nl">entry:</span>
<span class="nv">%4</span> <span
class="p">=</span> <span
class="k">tail</span> <span
class="k">call</span> <span
class="kt">i32</span> <span
class="vg">@llvm.amdgcn.workgroup.id.x</span><span
class="p">()</span>
<span class="nv">%5</span> <span
class="p">=</span> <span
class="k">tail</span> <span
class="k">call</span> <span
class="kt">i32</span> <span
class="vg">@llvm.amdgcn.workitem.id.x</span><span
class="p">()</span>
@@ -2722,14 +2722,14 @@ We are starting to look at performance optimization and
we expect more improveme
<span class="nv">%10</span> <span
class="p">=</span> <span
class="k">add</span> <span
class="k">nsw</span> <span
class="kt">i32</span> <span
class="nv">%.pre-phi</span><span
class="p">,</span> <span
class="nv">%5</span>
<span class="nv">%11</span> <span
class="p">=</span> <span
class="k">add</span> <span
class="k">nsw</span> <span
class="kt">i32</span> <span
class="nv">%.pre-phi</span><span
class="p">,</span> <span
class="nv">%5</span>
<span class="nv">%12</span> <span
class="p">=</span> <span
class="k">sext</span> <span
class="kt">i32</span> <span
class="nv">%11</span> <span
class="k">to</span> <span
class="kt">i64</span>
- <span class="nv">%13</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span class="k"> [...]
- <span class="nv">%14</span> <span
class="p">=</span> <span
class="k">load</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span
class="k">c</span><span
class="err">e</span> [...]
- <span class="nv">%15</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span class="k"> [...]
- <span class="nv">%16</span> <span
class="p">=</span> <span
class="k">load</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span
class="k">c</span><span
class="err">e</span> [...]
+ <span class="nv">%13</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span class="m"&g [...]
+ <span class="nv">%14</span> <span
class="p">=</span> <span
class="k">load</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span
class="m">1</span><span
class="p">)*</span> [...]
+ <span class="nv">%15</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span class="m"&g [...]
+ <span class="nv">%16</span> <span
class="p">=</span> <span
class="k">load</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span
class="m">1</span><span
class="p">)*</span> [...]
<span class="nv">%17</span> <span
class="p">=</span> <span
class="k">fadd</span> <span
class="kt">float</span> <span
class="nv">%14</span><span
class="p">,</span> <span
class="nv">%16</span>
<span class="nv">%18</span> <span
class="p">=</span> <span
class="k">sext</span> <span
class="kt">i32</span> <span
class="nv">%10</span> <span
class="k">to</span> <span
class="kt">i64</span>
- <span class="nv">%19</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span class="k"> [...]
- <span class="k">store</span> <span
class="kt">float</span> <span
class="nv">%17</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span
class="k">c</span><span
class="err">e</span><span
class="p">(</span> [...]
+ <span class="nv">%19</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span class="m"&g [...]
+ <span class="k">store</span> <span
class="kt">float</span> <span
class="nv">%17</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span
class="m">1</span><span
class="p">)*</span> <span
class="nv">%19</span [...]
<span class="k">br</span> <span
class="kt">label</span> <span
class="nv">%if_end</span>
diff --git a/index.html b/index.html
index e016019..f62e14c 100644
--- a/index.html
+++ b/index.html
@@ -148,7 +148,7 @@
<div id="tvm-banner-container">
<div id="tvm-banner-title">
<p>
- End to End Deep Learning Compiler Stack
+ Apache (incubating) TVM: An End to End Deep Learning Compiler Stack
</p>
<div id="tvm-banner-subtitle">
<p>
diff --git a/rss.xml b/rss.xml
index 898c09b..cdd32b2 100644
--- a/rss.xml
+++ b/rss.xml
@@ -5,8 +5,8 @@
<description>TVM - </description>
<link>https://tvm.apache.org</link>
<atom:link href="https://tvm.apache.org"; rel="self"
type="application/rss+xml" />
- <lastBuildDate>Sun, 22 Mar 2020 15:42:25 -0700</lastBuildDate>
- <pubDate>Sun, 22 Mar 2020 15:42:25 -0700</pubDate>
+ <lastBuildDate>Sun, 29 Mar 2020 11:17:22 -0700</lastBuildDate>
+ <pubDate>Sun, 29 Mar 2020 11:17:22 -0700</pubDate>
<ttl>60</ttl>
@@ -2691,13 +2691,13 @@ We are starting to look at performance optimization and
we expect more improveme
<p>You should see something like this:</p>
<figure class="highlight"><pre><code
class="language-llvm" data-lang="llvm"><span
class="c1">; ModuleID = 'myadd__kernel0'</span>
-<span class="err">sour</span><span
class="k">c</span><span
class="err">e_filename</span> <span
class="p">=</span> <span
class="s">"myadd__kernel0"</span>
+<span class="err">source_filename</span> <span
class="p">=</span> <span
class="s">"myadd__kernel0"</span>
<span class="k">target</span> <span
class="k">datalayout</span> <span
class="p">=</span> <span
class="s">"e-p:32:32-p1:64:64-p2:64:64-p3:32:32-p4:64:64-p5:32:32-i64:64-v16:16-v24:32-v32:32-v48:64-v96:128-v192:256-v256:256-v512:512-v1024:1024-v2048:2048-n32:64"</span>
<span class="k">target</span> <span
class="k">triple</span> <span
class="p">=</span> <span
class="s">"amdgcn-amd-amdhsa-hcc"</span>
<span class="c1">; Function Attrs: nounwind</span>
-<span class="k">define</span> <span
class="k">dllexport</span> <span
class="err">amdgpu_ker</span><span
class="k">ne</span><span
class="err">l</span> <span
class="kt">void</span> <span
class="vg">@myadd__kernel0</span><span
class="p">(</span><span
class="kt">float</span> <span class="k [...]
+<span class="k">define</span> <span
class="k">dllexport</span> <span
class="err">amdgpu_kernel</span> <span
class="kt">void</span> <span
class="vg">@myadd__kernel0</span><span
class="p">(</span><span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span class [...]
<span class="nl">entry:</span>
<span class="nv">%4</span> <span
class="p">=</span> <span
class="k">tail</span> <span
class="k">call</span> <span
class="kt">i32</span> <span
class="vg">@llvm.amdgcn.workgroup.id.x</span><span
class="p">()</span>
<span class="nv">%5</span> <span
class="p">=</span> <span
class="k">tail</span> <span
class="k">call</span> <span
class="kt">i32</span> <span
class="vg">@llvm.amdgcn.workitem.id.x</span><span
class="p">()</span>
@@ -2717,14 +2717,14 @@ We are starting to look at performance optimization and
we expect more improveme
<span class="nv">%10</span> <span
class="p">=</span> <span
class="k">add</span> <span
class="k">nsw</span> <span
class="kt">i32</span> <span
class="nv">%.pre-phi</span><span
class="p">,</span> <span
class="nv">%5</span>
<span class="nv">%11</span> <span
class="p">=</span> <span
class="k">add</span> <span
class="k">nsw</span> <span
class="kt">i32</span> <span
class="nv">%.pre-phi</span><span
class="p">,</span> <span
class="nv">%5</span>
<span class="nv">%12</span> <span
class="p">=</span> <span
class="k">sext</span> <span
class="kt">i32</span> <span
class="nv">%11</span> <span
class="k">to</span> <span
class="kt">i64</span>
- <span class="nv">%13</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span class="k"> [...]
- <span class="nv">%14</span> <span
class="p">=</span> <span
class="k">load</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span
class="k">c</span><span
class="err">e</span> [...]
- <span class="nv">%15</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span class="k"> [...]
- <span class="nv">%16</span> <span
class="p">=</span> <span
class="k">load</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span
class="k">c</span><span
class="err">e</span> [...]
+ <span class="nv">%13</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span class="m"&g [...]
+ <span class="nv">%14</span> <span
class="p">=</span> <span
class="k">load</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span
class="m">1</span><span
class="p">)*</span> [...]
+ <span class="nv">%15</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span class="m"&g [...]
+ <span class="nv">%16</span> <span
class="p">=</span> <span
class="k">load</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span
class="m">1</span><span
class="p">)*</span> [...]
<span class="nv">%17</span> <span
class="p">=</span> <span
class="k">fadd</span> <span
class="kt">float</span> <span
class="nv">%14</span><span
class="p">,</span> <span
class="nv">%16</span>
<span class="nv">%18</span> <span
class="p">=</span> <span
class="k">sext</span> <span
class="kt">i32</span> <span
class="nv">%10</span> <span
class="k">to</span> <span
class="kt">i64</span>
- <span class="nv">%19</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span class="k"> [...]
- <span class="k">store</span> <span
class="kt">float</span> <span
class="nv">%17</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">add</span><span
class="err">rspa</span><span
class="k">c</span><span
class="err">e</span><span
class="p">(</span> [...]
+ <span class="nv">%19</span> <span
class="p">=</span> <span
class="k">getelementptr</span> <span
class="k">inbounds</span> <span
class="kt">float</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span class="m"&g [...]
+ <span class="k">store</span> <span
class="kt">float</span> <span
class="nv">%17</span><span
class="p">,</span> <span
class="kt">float</span> <span
class="k">addrspace</span><span
class="p">(</span><span
class="m">1</span><span
class="p">)*</span> <span
class="nv">%19</span [...]
<span class="k">br</span> <span
class="kt">label</span> <span
class="nv">%if_end</span>
diff --git a/vta.html b/vta.html
index 35b23c5..695f9fc 100644
--- a/vta.html
+++ b/vta.html
@@ -151,7 +151,7 @@
<h1 id="about-vta">About VTA</h1>
-<p>The Versatile Tensor Accelerator (VTA) is an extension of the TVM framework
designed to advance deep learning and hardware innovation.
+<p>The Versatile Tensor Accelerator (VTA) is an extension of the
Apache(incubating) TVM framework designed to advance deep learning and hardware
innovation.
VTA is a programmable accelerator that exposes a RISC-like programming
abstraction to describe compute and memory operations at the tensor level. We
designed VTA to expose the most salient and common characteristics of
mainstream deep learning accelerators, such as tensor operations, DMA
load/stores, and explicit compute/memory arbitration.</p>
<p>VTA is more than a standalone accelerator design: it’s an end-to-end
solution that includes drivers, a JIT runtime, and an optimizing compiler stack
based on TVM.
@@ -169,10 +169,12 @@ This forms a truly end-to-end, from software-to-hardware
open source stack for d
</ul>
<p>VTA is a component of TVM which was a research project at the <a
href="https://sampl.cs.washington.edu/";>SAMPL group</a> of
-Paul G. Allen School of Computer Science & Engineering, University of
Washington. The project is now driven by an open source community involving
multiple industry and academic institutions.
-The project adopts <a
href="https://docs.tvm.ai/contribute/community.html";>Apache-style merit based
governace model</a>.</p>
+Paul G. Allen School of Computer Science & Engineering, University of
Washington.
+TVM is now an effort undergoing incubation at The Apache Software Foundation
(ASF),
+driven by an open source community involving multiple industry and academic
institutions
+under the Apache way.</p>
-<p>Read more about VTA in our <a
href="https://tvm.ai/2018/07/12/vta-release-announcement.html";>TVM blog
post</a>, or in the <a href="https://arxiv.org/abs/1807.04188";>VTA
techreport</a>.</p>
+<p>Read more about VTA in the <a
href="https://tvm.ai/2018/07/12/vta-release-announcement.html";>TVM blog
post</a>, or in the <a href="https://arxiv.org/abs/1807.04188";>VTA
techreport</a>.</p>
</div>
</div>
