Frequently asked questions summary

Preliminary Proposal and Task Results Submission

Q1 How to submit the preliminary contest results data?
Answer: You can use FTP to upload your preliminary contest results data. The address of the FPT server is: We highly recommend that all teams using the FTP client to connect FTP server, such as FlashFXPFileZilla etc. The FTP account and password have sent to the email of team advisor and team leader. If you fail to receive this information, please send email to
If you are Outside mainland China and have problems with FTP uploading, you can choose network disk such as OneDrive and deliver the address to us in your proposal.
The FTP servers using Cloud hosts. The maximum bandwidth is 50Mb/s. So we suggest you upload your results data as early as you can. Or upload the largest data files in advance. 
Please send your Proposal to Also upload it to FTP server. For CSEM and SISC results data only upload on FTP server.


Language Exam (LE)

Q1: We wonder whether use FPGA or combine FPGA with GPU accelerate cards is permitted to optimize computing tasks in ASC preliminary round? Could FPGA associated computing machine be used in the final round?

Answer: FPGA devices or combine FPGA with GPU can be used in preliminary round and final round, but the compatibility of hardware and software needs to be solved by yourself.


Q2: For the language exam (LE) challenge, it has 30 points in ASC20, its score in ASC20-21 has been adjusted to 22.5 points, but the coefficient of the score calculation formula you published is still 30 instead of 22.5. Is this the final calculation

Answer:The coefficient in the score calculation formula needs to be changed from 30 to 22.5. This is our mistake.


Q3: can we adjust and increase the datasets by ourselves? Can we use CLOTH dataset as training dataset?

Answer: Our training dataset already include CLOTH dataset. Other datasets are not permitted to use.


Q4: Whether DeepSpeed can be used in the third question of ASC?
Answer:The DeepSpeed API is a lightweight wrapper on PyTorch. It will be allowed to be used.


Q5: In the task description you already mention various transformer networks. Are there any restrictions to this, i.e. are there any restrictions on the data we may use?
Answer:It is allowed to use pre-trained models such as BERT, ROBERTA.It is forbidden to use additional datasets to train your model.


Q6: The test set does not give the correct answer. We can predict the answer, but how to calculate the score of Stest. We can calculate the model accuracy by the answer of dev set.
Answer:The score of Stest is the accuracy of test dataset



Q1:Should we optimize the source of the QuEST or two contest cases random.c and GHZ_QFT.c?
Answer:The allowed modification to the source code excludes the provided circuit code. Because the provided circuit just like the calculating models, you can’t change it. Please do some optimizations related to the algorithm or others. But don’t change the provided circuit code, or the zero score will be got!

Q2:For the QuEST problem, we have known that some optimization techniques would cause error(for example, using GPU). May I ask for the final result, whether small error under a certain limit could tolerated or we need to keep the result precise?
Answer: The final results must be the exactly same as the referenced results. You should keep the answer precise. In this case, the GPU acceleration may cause some errors has no relationship to optimization.

Q3:We found there are various versions of QuEST. At present, we are using QuEST 3.0. Will it affect the verification of the output result?
Answer: “We strongly recommend using the stable version of QuEST_2.1.0 and the corresponding source code is available in Reference2”.You can see the last part of Application Background of the QuEST challenge in . Please read it carefully.

Q4:The QuEST has a latest version v3.0.1. We wonder whether we could use the latest version instead of v2.1.0, and if not could you tell us what's wrong in the program?
Answer:We still recommend the version 2.1.0 for this competition.The competition just focus on the optimization of algorithm for improving the performance of application. It doesn’t matter with version of application. We have done many tests using the version 2.1.0. It is fair to every participant using the same version of application for competition.

Q5:Can random and GHZ quantum circuits be simplified, decomposed, and then calculated?It's like simplifying the math and then calculating it.
Answer:The provided circuit (GHZ_QFT.cor random.c) can’t be modified. Any changes to the provided circuit is not allowed. Or you will get zero score.



Q1: Which version of the software Presto the organizing committee used for running and testing the

Answer: There is no restriction for the version of PRESTO software. However, we suggest using the latest version and encourage teams to optimize on this basis.


Q2: Where to download the input data of PRESTO test?

Answer: The Input data of all tasks can be download from Baidu: (password: fhd4) or Microsoft OneDrive!Ar_0HIDyftZTsBiXPJUtGfiMmTom?e=w7VPAx.


Q3: How can we determine the correctness of the results from the example script

Answer: After installing PRESTO software, we suggest the team first run all the test examples in PRESTO software to check the correctness of the installation. Then the example script could generate correct result files.


Q4: How to check the correctness of the source code in PRESTO if we commit some changes and optimization?

Answer: There is no way to check to correctness of PRESTO software except its original examples and test scripts. So if the team make any changes or optimization, a verification process should also be included in the final proposal.

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