Presenter: Shintaro Momose, Director, Quantum Computing Business Department, NEC Corporation
< Abstract >
This presentation shows NEC’s quantum computing strategies, development status of quantum computing machine, and NEC's current products to provide higher sustained performance in the annealing/optimization fields. 
NEC developed the Aurora Vector Annealer as a digital annealer working on the SX-Aurora TSUBASA supercomputer and has a strong business relationship with D-Wave providing a quantum annealer. 
NEC aims at solving various social issues by using the quantum/digital annealing technologies and by developing a hybrid platform with supercomputer and quantum/digital annealer to provide much higher sustained performance.

Presenter: Vincent Etienne, Benchmarking Analyst, NEC Deutschland GmbH
< Abstract >
The reduction of greenhouse gas emissions to limit the global temperature increase is a major challenge for our society. Most of governments have setup roadmaps to reduce their carbon footprint in the near future. To reach these objectives, Oil & Gas companies are expected to play a pivotal role. At present, we witness significant investments from these companies to develop renewable energies besides the exploitation of fossil resources. 
In this talk, we discuss the computing requirements of traditional applications in the energy sector. We investigate how renewable energies could impact the HPC ecosystem with the introduction of novel algorithms. For each application, we discuss its compute footprint and show it can be handled efficiently on the NEC SX-Aurora TSUBASA Vector Engine, an architecture specially designed for HPC workloads.

Presenter: Nicolas Weber, Senior Research Engineer, NEC Laboratories Europe GmbH
< Abstract >
The Vector Engine Driver API (VEDA) was developed to enable easy porting of existing CUDA applications to NEC's SX-Aurora TSUBASA. While the API enables a smooth transition between the different architectures, there are unique features that require special attention, to achieve optimal performance.

In this presentation we show multiple methods to improve your code. First, we explain how to use C++ function overloading and templates. Second, we show how to make best use of the unique features of VEDAdeviceptrs. Third, we explain our improvements for VEDA's memset and memcopy operations, that can also improve your own code.

Presenter: Deepak Pathania, Manager (Business Development/Enablement), NEC Corporation India
< Abstract >
Resource exploration planning optimization is a difficult problem which cannot be solved by classical computers today. Such problems are referred to as combinatorial optimization problems (NPHard), typically solved by quantum annealer or computers. Exploration drilling planning is one such challenge that if addressed correctly can yield tremendous benefits in terms of improved success ratio and rescued cost and resources required. Since, using an actual quantum computer is limited today by hardware availability for real-world applications, quantum inspired classical computers (QuICC) can be helpful either working independently or in a hybrid fashion, in combination with a quantum computer. In this presentation, we share how a QuICC solution can independently solve this NP-hard problem. We demonstrate using Simulated Annealing on vector engine-based accelerator system as a QuICC solution which can solve exploration drilling planning problem, with similar construction as a travelling salesman (TSP) or a combinatorial optimization problem.

Presenter: Kosuke Tomonaga, Collaborative Researcher, The University of Tokyo / SoftBank Robotics Corp.
< Abstract >
In the previous SC21 and ISC2022, we introduced our efforts to implement an artificial ego using an extended Riemann sphere on the SX-Aurora TSUBASA.

In this presentation, we will show how we realized the concept of "Mobility for All" as a result of the initial AE installed in a racing vehicle. In our experiment, 29 subjects, including people with disabilities, evaluated the AE vehicle and gave it a very high score of 9 out of 10.

In the future we plan to measure the moral dimension by calculating the synchronization rate between the emotions of the vehicle, the emotions of the driver, and the emotions of the fans.