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Because operators have different costs on different AI chips, all optimization strategies for different AI chips are different. The network configuration of different hardware is different, so how to automatically generate the precision adjustment strategy that adapts to various hardware, especially the low bit strategy has become a difficult problem. + +## Target: + +​ Self-adaptively provides a low-bit precision training mechanism for various networks. + +![target](target.PNG) + +## Method: + +​ We expect the applicant can conduct low-bit neural networks training research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From 51ec4130fbae93be38938445c88a687eb328f249 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:46:35 +0800 Subject: [PATCH 08/27] add working-groups/research/Topic2: Memory Optimization. --- .../research/Topic2: Memory Optimization | 22 +++++++++++++++++++ 1 file changed, 22 insertions(+) create mode 100644 working-groups/research/Topic2: Memory Optimization diff --git a/working-groups/research/Topic2: Memory Optimization b/working-groups/research/Topic2: Memory Optimization new file mode 100644 index 0000000..074cb61 --- /dev/null +++ b/working-groups/research/Topic2: Memory Optimization @@ -0,0 +1,22 @@ +# Topic2: Memory Optimization + +## Motivation: + +​ There are many strategies for memory optimization, such as recalculation and host-device memory switching. These strategies further break through the memory bottleneck by increasing the amount of calculation and increase the batchsize. Increasing batchsize can often improve the utilization of GPU and NPU to improve throughput performance. + +## Target: + +* Adaptive search memory optimization strategy to optimize the overall network performance. + +* Or provide a methodological strategy. + + ![memor_opt](memor_opt.PNG) + +## Method: + +​ We expect the applicant can conduct memory optimization research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From 76e2d00b91e099bdc2c8694b4dad08ae661916a7 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:47:20 +0800 Subject: [PATCH 09/27] =?UTF-8?q?=E5=88=A0=E9=99=A4=E6=96=87=E4=BB=B6=20wo?= =?UTF-8?q?rking-groups/research/Topic2:=20Memory=20Optimization?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../research/Topic2: Memory Optimization | 22 ------------------- 1 file changed, 22 deletions(-) delete mode 100644 working-groups/research/Topic2: Memory Optimization diff --git a/working-groups/research/Topic2: Memory Optimization b/working-groups/research/Topic2: Memory Optimization deleted file mode 100644 index 074cb61..0000000 --- a/working-groups/research/Topic2: Memory Optimization +++ /dev/null @@ -1,22 +0,0 @@ -# Topic2: Memory Optimization - -## Motivation: - -​ There are many strategies for memory optimization, such as recalculation and host-device memory switching. These strategies further break through the memory bottleneck by increasing the amount of calculation and increase the batchsize. Increasing batchsize can often improve the utilization of GPU and NPU to improve throughput performance. - -## Target: - -* Adaptive search memory optimization strategy to optimize the overall network performance. - -* Or provide a methodological strategy. - - ![memor_opt](memor_opt.PNG) - -## Method: - -​ We expect the applicant can conduct memory optimization research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. - -## How To Join - -1. Submit an issue/PR based on community discussion for consultation or claim on related topics -2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From 433737de3f21f9732f5da0c6f0b2d2862c021831 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:47:33 +0800 Subject: [PATCH 10/27] =?UTF-8?q?=E9=87=8D=E5=91=BD=E5=90=8D=20working-gro?= =?UTF-8?q?ups/research/Low-bit=20Neural=20Networks=20Training.md=20?= =?UTF-8?q?=E4=B8=BA=20working-groups/research/Topic1:Low-bit=20Neural=20N?= =?UTF-8?q?etworks=20Training.md?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...rks Training.md => Topic1:Low-bit Neural Networks Training.md} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename working-groups/research/{Low-bit Neural Networks Training.md => Topic1:Low-bit Neural Networks Training.md} (100%) diff --git a/working-groups/research/Low-bit Neural Networks Training.md b/working-groups/research/Topic1:Low-bit Neural Networks Training.md similarity index 100% rename from working-groups/research/Low-bit Neural Networks Training.md rename to working-groups/research/Topic1:Low-bit Neural Networks Training.md -- Gitee From 27cf1dce39efb1dd92472154e67e02f0cef40b77 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:48:03 +0800 Subject: [PATCH 11/27] add working-groups/research/Topic2: Memory Optimization.md. --- .../research/Topic2: Memory Optimization.md | 22 +++++++++++++++++++ 1 file changed, 22 insertions(+) create mode 100644 working-groups/research/Topic2: Memory Optimization.md diff --git a/working-groups/research/Topic2: Memory Optimization.md b/working-groups/research/Topic2: Memory Optimization.md new file mode 100644 index 0000000..074cb61 --- /dev/null +++ b/working-groups/research/Topic2: Memory Optimization.md @@ -0,0 +1,22 @@ +# Topic2: Memory Optimization + +## Motivation: + +​ There are many strategies for memory optimization, such as recalculation and host-device memory switching. These strategies further break through the memory bottleneck by increasing the amount of calculation and increase the batchsize. Increasing batchsize can often improve the utilization of GPU and NPU to improve throughput performance. + +## Target: + +* Adaptive search memory optimization strategy to optimize the overall network performance. + +* Or provide a methodological strategy. + + ![memor_opt](memor_opt.PNG) + +## Method: + +​ We expect the applicant can conduct memory optimization research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From 3e73994e78f8c13f2acb2ac2c076e1220f69bd5d Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:49:46 +0800 Subject: [PATCH 12/27] =?UTF-8?q?add=20working-groups/research/Topic3?= =?UTF-8?q?=EF=BC=9AModel=20Innovation.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../Topic3\357\274\232Model Innovation" | 22 +++++++++++++++++++ 1 file changed, 22 insertions(+) create mode 100644 "working-groups/research/Topic3\357\274\232Model Innovation" diff --git "a/working-groups/research/Topic3\357\274\232Model Innovation" "b/working-groups/research/Topic3\357\274\232Model Innovation" new file mode 100644 index 0000000..fa59dc0 --- /dev/null +++ "b/working-groups/research/Topic3\357\274\232Model Innovation" @@ -0,0 +1,22 @@ +# Topic3：Model Innovation + +## Motivation： + +1. In-depth probability model innovation: through the combination of neural network and probability model, the model can better help decision-making. +2. Graph neural network: The neural network is combined with the traditional graph structure, oriented to cognitive reasoning and future trends. +3. Model innovation combining traditional models and neural networks is a research hotspot. + +## Target： + +- Complete probability sampling library and probability inference (learning the probability distribution of the overall sample through known samples) algorithm library +- Design new algorithms for dynamically changing heterogeneous graphs (different feature dimensions and different information aggregation methods) +- Trillion distributed graph data storage, segmentation and sampling + +## Method： + +​ We expect the applicant can conduct model innovation research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join： + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From f5d310b62ce1793a5b4d5698bc2a71f1816d2ef2 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:49:57 +0800 Subject: [PATCH 13/27] =?UTF-8?q?=E9=87=8D=E5=91=BD=E5=90=8D=20working-gro?= =?UTF-8?q?ups/research/Topic3=EF=BC=9AModel=20Innovation=20=E4=B8=BA=20wo?= =?UTF-8?q?rking-groups/research/Topic3=EF=BC=9AModel=20Innovation.md?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../research/Topic3\357\274\232Model Innovation.md" | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename "working-groups/research/Topic3\357\274\232Model Innovation" => "working-groups/research/Topic3\357\274\232Model Innovation.md" (100%) diff --git "a/working-groups/research/Topic3\357\274\232Model Innovation" "b/working-groups/research/Topic3\357\274\232Model Innovation.md" similarity index 100% rename from "working-groups/research/Topic3\357\274\232Model Innovation" rename to "working-groups/research/Topic3\357\274\232Model Innovation.md" -- Gitee From e567f93eaccdd9dbf90c865fa9dfa17026934d14 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:50:15 +0800 Subject: [PATCH 14/27] =?UTF-8?q?=E9=87=8D=E5=91=BD=E5=90=8D=20working-gro?= =?UTF-8?q?ups/research/Topic3=EF=BC=9AModel=20Innovation.md=20=E4=B8=BA?= =?UTF-8?q?=20working-groups/research/Topic3:Model=20Innovation.md?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../research/Topic3:Model Innovation.md | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename "working-groups/research/Topic3\357\274\232Model Innovation.md" => working-groups/research/Topic3:Model Innovation.md (100%) diff --git "a/working-groups/research/Topic3\357\274\232Model Innovation.md" b/working-groups/research/Topic3:Model Innovation.md similarity index 100% rename from "working-groups/research/Topic3\357\274\232Model Innovation.md" rename to working-groups/research/Topic3:Model Innovation.md -- Gitee From 64a79c33ef97a103426897130a7a2ed3d9c94afc Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:50:26 +0800 Subject: [PATCH 15/27] =?UTF-8?q?=E9=87=8D=E5=91=BD=E5=90=8D=20working-gro?= =?UTF-8?q?ups/research/Topic2:=20Memory=20Optimization.md=20=E4=B8=BA=20w?= =?UTF-8?q?orking-groups/research/Topic2:Memory=20Optimization.md?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...pic2: Memory Optimization.md => Topic2:Memory Optimization.md} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename working-groups/research/{Topic2: Memory Optimization.md => Topic2:Memory Optimization.md} (100%) diff --git a/working-groups/research/Topic2: Memory Optimization.md b/working-groups/research/Topic2:Memory Optimization.md similarity index 100% rename from working-groups/research/Topic2: Memory Optimization.md rename to working-groups/research/Topic2:Memory Optimization.md -- Gitee From a093e8601187d5fbd2f666e47a5248d16def516d Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:50:56 +0800 Subject: [PATCH 16/27] =?UTF-8?q?add=20working-groups/research/Topic3?= =?UTF-8?q?=EF=BC=9AAI=20for=20Scientific=20Computing.md.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...357\274\232AI for Scientific Computing.md" | 20 +++++++++++++++++++ 1 file changed, 20 insertions(+) create mode 100644 "working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" diff --git "a/working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" "b/working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" new file mode 100644 index 0000000..8f96f11 --- /dev/null +++ "b/working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" @@ -0,0 +1,20 @@ +# Topic2：AI for Scientific Computing + +## Motivation： + +* AI modeling ：AI automatic modeling can effectively improve modeling efficiency, and convergence analysis can improve model reliability and ensure simple and safe use by users. +* AI solution：The calculation amount of high-order differential increases exponentially with the parameter and the order. We can design neural network models to solve such classic problems. + +## Target： + + * AI modeling：Construct a neural network, training data and Loss function for scientific computing problems. + * AI solution：AI model solves differential equations, solves optimization problems, achieve the goal that the amount of high-order automatic differential calculation increases linearly with the order. + +## Method： + +​ We expect the applicant can conduct AI for scientific computing research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join： + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From a5c213f4a18e8cc20674aedd501e29b68e8f19c7 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:51:08 +0800 Subject: [PATCH 17/27] =?UTF-8?q?update=20working-groups/research/Topic3?= =?UTF-8?q?=EF=BC=9AAI=20for=20Scientific=20Computing.md.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../research/Topic3\357\274\232AI for Scientific Computing.md" | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git "a/working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" "b/working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" index 8f96f11..3fc91e1 100644 --- "a/working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" +++ "b/working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" @@ -1,4 +1,4 @@ -# Topic2：AI for Scientific Computing +# Topic3：AI for Scientific Computing ## Motivation： -- Gitee From fc44c73d2be2b259b7f88ac0f1adfba532e81278 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:51:25 +0800 Subject: [PATCH 18/27] =?UTF-8?q?=E9=87=8D=E5=91=BD=E5=90=8D=20working-gro?= =?UTF-8?q?ups/research/Topic3=EF=BC=9AAI=20for=20Scientific=20Computing.m?= =?UTF-8?q?d=20=E4=B8=BA=20working-groups/research/Topic4:AI=20for=20Scien?= =?UTF-8?q?tific=20Computing.md?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../research/Topic4:AI for Scientific Computing.md | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename "working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" => working-groups/research/Topic4:AI for Scientific Computing.md (100%) diff --git "a/working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" b/working-groups/research/Topic4:AI for Scientific Computing.md similarity index 100% rename from "working-groups/research/Topic3\357\274\232AI for Scientific Computing.md" rename to working-groups/research/Topic4:AI for Scientific Computing.md -- Gitee From f52ea8d17c23599dc2930737d4218e064f715b68 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:51:35 +0800 Subject: [PATCH 19/27] update working-groups/research/Topic4:AI for Scientific Computing.md. --- working-groups/research/Topic4:AI for Scientific Computing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/working-groups/research/Topic4:AI for Scientific Computing.md b/working-groups/research/Topic4:AI for Scientific Computing.md index 3fc91e1..337573e 100644 --- a/working-groups/research/Topic4:AI for Scientific Computing.md +++ b/working-groups/research/Topic4:AI for Scientific Computing.md @@ -1,4 +1,4 @@ -# Topic3：AI for Scientific Computing +# Topic4：AI for Scientific Computing ## Motivation： -- Gitee From 33e047adb62ff52a3a336b89adc236416eb558c4 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:55:28 +0800 Subject: [PATCH 20/27] add working-groups/research/Topic5:Verifiable Trustworthy AI.md. --- .../Topic5:Verifiable Trustworthy AI.md | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) create mode 100644 working-groups/research/Topic5:Verifiable Trustworthy AI.md diff --git a/working-groups/research/Topic5:Verifiable Trustworthy AI.md b/working-groups/research/Topic5:Verifiable Trustworthy AI.md new file mode 100644 index 0000000..b108c26 --- /dev/null +++ b/working-groups/research/Topic5:Verifiable Trustworthy AI.md @@ -0,0 +1,19 @@ +# Topic5: Verifiable Trustworthy AI + +## Motivation: + +- Many aspects of trustworthy AI (or responsible AI), such as robustness, backdoor-free, fairness, privacy protection capabilities, and accountability, have gradually attracted the attention of the industry and academia. +- Scholars' understanding and research on the attributes of trustworthy AI are mostly empirical, and there are few theoretical studies. The verifiable and certifiable analysis, tuning, and evaluation methods of trustworthy AI attributes and bounds, and their relation to explainable AI, require theoretical guidance. + +## Target: + +​ Propose verifiable and certifiable research mechanism and evaluation system on trustworthy AI. + +## Method: + +​ We expect the applicant can conduct Verifiable Trustworthy AI research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From c32ca0fbe17b727b57c65430a8e175ad4e2f87a2 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 11:56:14 +0800 Subject: [PATCH 21/27] add working-groups/research/Topic6: Confidential AI Computing.md. --- .../Topic6: Confidential AI Computing.md | 20 +++++++++++++++++++ 1 file changed, 20 insertions(+) create mode 100644 working-groups/research/Topic6: Confidential AI Computing.md diff --git a/working-groups/research/Topic6: Confidential AI Computing.md b/working-groups/research/Topic6: Confidential AI Computing.md new file mode 100644 index 0000000..e8df265 --- /dev/null +++ b/working-groups/research/Topic6: Confidential AI Computing.md @@ -0,0 +1,20 @@ +# Topic6: Confidential AI Computing + +## Motivation: + +- In the training and deployment process of AI services, several vital resources such as data, models, and computing resources may belong to different parties, so a large amount of data will move across trust domains. The problems of data privacy protection and model confidentiality protection are prominent. +- Confidential computing is an important direction to protect the confidentiality of key data. At present, confidential computing based on trusted execution environment has performance advantages, but its trust model is limited; the trust model of confidential computing based on cryptography (homomorphic encryption, multi-party computing) is simple, but there is still a gap between performance and practicality. +- A series of specialized optimizations may improve the performance of confidential computing in AI scenarios, including but not limited to: cryptography suitable for AI, specialized intermediate representation and compling strategy for confidential AI computing, and hardware-based acceleration. + +## Target: + +​ Realize an AI on Encrypted Data & Model computing framework with feasible, flexible and efficient performance in actual AI application scenarios, or key technologies. + +## Method: + +​ We expect the applicant can conduct Confidential AI Computing research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From cee9fde0f34eebc3f912da982bf67cbaffe2e2b5 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 14:09:59 +0800 Subject: [PATCH 22/27] add working-groups/research/Topic7: Tensor Differentiable Calculation Framework.md. --- ...or Differentiable Calculation Framework.md | 21 +++++++++++++++++++ 1 file changed, 21 insertions(+) create mode 100644 working-groups/research/Topic7: Tensor Differentiable Calculation Framework.md diff --git a/working-groups/research/Topic7: Tensor Differentiable Calculation Framework.md b/working-groups/research/Topic7: Tensor Differentiable Calculation Framework.md new file mode 100644 index 0000000..47b9121 --- /dev/null +++ b/working-groups/research/Topic7: Tensor Differentiable Calculation Framework.md @@ -0,0 +1,21 @@ +# Topic7: Tensor Differentiable Calculation Framework + +## Motivation: + +* The new network model poses challenges to the IR expression, optimization and execution of the deep learning framework, including the introduction of a new op abstraction level, and the dynamics of the model. +* Third-party high-performance computing languages or frameworks are accelerated, and there is an urgent need for a more versatile and open tensor computing framework and API design +* The technical challenges of unified optimization of the model layer and the operator layer, including hierarchical IR design, optimization of infrastructure, automatic tuning, loop optimization, etc. +* Differential equations are solved with a large number of differentials, which have high requirements for the differential expression of the framework, interface design, algorithm analysis efficiency and reliability. + +##Target: + +​ Driven by cutting-edge applications, from the perspectives of new models, dynamic models, high-performance computing languages, etc., study the evolution direction and key technology paths of future computing frameworks. For example, it supports differentiable programming of high-order differentiation and is compatible with traditional Fortran/C numerical calculation framework. + +##Method: + +​ We expect the applicant can conduct tensor differentiable calculation framework research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From e45d9b270c6fa63a94ac06017700476e9b190a82 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 14:10:14 +0800 Subject: [PATCH 23/27] =?UTF-8?q?=E9=87=8D=E5=91=BD=E5=90=8D=20working-gro?= =?UTF-8?q?ups/research/Topic6:=20=20Confidential=20AI=20Computing.md=20?= =?UTF-8?q?=E4=B8=BA=20working-groups/research/Topic6:Confidential=20AI=20?= =?UTF-8?q?Computing.md?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...ential AI Computing.md => Topic6:Confidential AI Computing.md} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename working-groups/research/{Topic6: Confidential AI Computing.md => Topic6:Confidential AI Computing.md} (100%) diff --git a/working-groups/research/Topic6: Confidential AI Computing.md b/working-groups/research/Topic6:Confidential AI Computing.md similarity index 100% rename from working-groups/research/Topic6: Confidential AI Computing.md rename to working-groups/research/Topic6:Confidential AI Computing.md -- Gitee From 178bf166c649853c52c6e55ff768c6db229c9a81 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 14:10:48 +0800 Subject: [PATCH 24/27] add working-groups/research/Topic8:Distributed And Parallel AI Computing Framework.md. --- ...ted And Parallel AI Computing Framework.md | 20 +++++++++++++++++++ 1 file changed, 20 insertions(+) create mode 100644 working-groups/research/Topic8:Distributed And Parallel AI Computing Framework.md diff --git a/working-groups/research/Topic8:Distributed And Parallel AI Computing Framework.md b/working-groups/research/Topic8:Distributed And Parallel AI Computing Framework.md new file mode 100644 index 0000000..80df83f --- /dev/null +++ b/working-groups/research/Topic8:Distributed And Parallel AI Computing Framework.md @@ -0,0 +1,20 @@ +# Topic8:Distributed And Parallel AI Computing Framework + +## Motivation: + +* The scale and complexity of models are getting higher and higher, such as GPT-3 with 175 billion parameters, millions of face recognition, and tens of billions of feature recommendations. +* It is difficult to split the model manually. For example, developers need to combine information such as calculation amount, cluster size, communication bandwidth, and network topology to construct a parallel mode. +* The expression of the parallel mode lacks adaptability, and the simple graph-level model segmentation cannot obtain high-efficiency speedup. It requires the decoupling of algorithm logic and parallel logic. + +## Target: + +​ Driven by super-large models, research key technologies for accelerating distributed training, including but not limited to automatic parallelism, hybrid parallelism, memory optimization, and elastic scaling. Such as achieving heterogeneous automatic parallel efficiency and linear speedup. + +## Method: + +​ We expect the applicant can conduct distributed and parallel AI computing framework research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From c66d781c33d8132049b0d1ecda5fd45d33b374a3 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 14:41:44 +0800 Subject: [PATCH 25/27] =?UTF-8?q?add=20working-groups/research/Topic9:Expl?= =?UTF-8?q?ainable=C2=A0AI.md.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../research/Topic9:Explainable\302\240AI.md" | 20 +++++++++++++++++++ 1 file changed, 20 insertions(+) create mode 100644 "working-groups/research/Topic9:Explainable\302\240AI.md" diff --git "a/working-groups/research/Topic9:Explainable\302\240AI.md" "b/working-groups/research/Topic9:Explainable\302\240AI.md" new file mode 100644 index 0000000..cdc3c2f --- /dev/null +++ "b/working-groups/research/Topic9:Explainable\302\240AI.md" @@ -0,0 +1,20 @@ +# Topic9：Explainable AI + +##Motivation： + +​ The current deep learning model is essentially black box due to its technical complexity , which leads to the opacity and inexplicability of AI services and further restricts the commercial application and promotion of AI services. Existing interpretable AI technology mainly focuses on how to provide limited engineering auxiliary information to the model, but ignores the understanding of AI models from the perspective of human cognition + +​ Humans usually understand things through analogies, metaphors, induction and other cognitive methods, and have a certain process of mental cognition construction. Thus, in this project, we expect to be able to explore more systematic and interpretable AI methods that conform to human cognition, including interactive interfaces, interpretation methods, measurement methods, and so on. + +##Target： + +​ A complete set of interpretable AI methods and strategies in line with human cognition, providing necessary interactive cognitive interface design solutions for different scenarios and different cognitions, and a case study for typical scenarios. + +## Method： + +​ We expect the applicant can conduct XAI research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join： + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com \ No newline at end of file -- Gitee From f21fbda5bcf31b9eee4f746b3da899195e714f01 Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 14:42:21 +0800 Subject: [PATCH 26/27] add working-groups/research/Topic10:AutoML.md. --- working-groups/research/Topic10:AutoML.md | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) create mode 100644 working-groups/research/Topic10:AutoML.md diff --git a/working-groups/research/Topic10:AutoML.md b/working-groups/research/Topic10:AutoML.md new file mode 100644 index 0000000..eacbead --- /dev/null +++ b/working-groups/research/Topic10:AutoML.md @@ -0,0 +1,20 @@ +#Topic10：AutoML + +## Motivation： + +​ Nowadays, training a model that meets the accuracy requirements often requires rich expert knowledge and repeated iterative attempts. Although there is AutoML technology, there are still problems of difficult search space setting and long training time for large search spaces. If you can combine the iterative history of user training and analyze historical data, a lightweight hyperparameter recommendation method can be realized, which can greatly improve the developer experience. + +​ Similarly, for performance tuning, there are similar problems. In different heterogeneous hardware, models, and data processing scenarios, expert knowledge is required for tuning. Therefore, we aim to reduce the performance tuning threshold by automatically identifying system performance bottlenecks and recommending the best code path. + +## Target： + +​ Reduce model development cost, set up thresholds through automatic hyper-parameter configuration and performance optimization paths, and improve model debugging and optimization efficiency. + +## Method： + +​ We expect the applicant can conduct AutoML research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and provide you with the most powerful technical support. + +## How To Join： + +1. Submit an issue/PR based on community discussion for consultation or claim on related topics +2. Submit your proposal to us by email xxx@huawei.com -- Gitee From ac511444dd394dfa7e10876db27a8f25dd6bc46e Mon Sep 17 00:00:00 2001 From: godbaiqi Date: Mon, 17 Aug 2020 14:42:50 +0800 Subject: [PATCH 27/27] update working-groups/research/Topic10:AutoML.md. --- working-groups/research/Topic10:AutoML.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/working-groups/research/Topic10:AutoML.md b/working-groups/research/Topic10:AutoML.md index eacbead..484d583 100644 --- a/working-groups/research/Topic10:AutoML.md +++ b/working-groups/research/Topic10:AutoML.md @@ -1,4 +1,4 @@ -#Topic10：AutoML +# Topic10：AutoML ## Motivation： -- Gitee