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  4. Unleashing the Full Potential of GPUs With Arc Compute

Unleashing the Full Potential of GPUs With Arc Compute

Arc Compute optimizes GPU performance and utilization for AI and HPC workloads, reducing hardware requirements and environmental impact.

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Tom Smith user avatar
Tom Smith
DZone Core CORE ·
Jun. 21, 24 · News
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In the realm of artificial intelligence (AI) and high-performance computing (HPC), GPUs have become an indispensable resource. However, as the demand for accelerated hardware grows, organizations face challenges in maximizing GPU performance and utilization while minimizing costs and environmental impact. Enter Arc Compute, a company dedicated to harnessing low-level optimization techniques to achieve peak efficiency and performance in GPU-driven workloads.

Micheal Buchel, CTO of Arc Compute, recently introduced his company to the 56th IT Press Tour.

The GPU Inefficiency Problem

Arc Compute's journey began with the discovery of significant GPU inefficiencies within existing systems. Traditional solutions, such as job schedulers and fractional GPU software, often fail to address the core issues, leading to suboptimal performance and resource underutilization. Organizations are left with limited options: ignore the problem, invest in incomplete software solutions, purchase additional hardware, or resort to manual task matching — a time-consuming and error-prone process.

Introducing the ArcHPC Suite

To tackle these challenges head-on, Arc Compute developed the ArcHPC Suite, a collection of innovative tools designed to maximize GPU performance and utilization. At the heart of this suite are three key components: Nexus, Oracle, and Mercury.

Nexus: The Foundation for Optimization

ArcHPC Nexus serves as the foundation for the entire suite, providing a management solution for advanced GPUs and other accelerated hardware. By creating an optimal environment for GPU utilization and performance, Nexus eliminates the limitations and performance degradation pitfalls commonly encountered in other solutions.

Nexus seamlessly integrates with popular job schedulers like Slurm, enabling users to maximize task density and GPU performance without the need for manual intervention. Through intelligent resource allocation and granular control over GPU environments, Nexus ensures tasks are efficiently matched and executed, reducing the notorious "North Star Metric problem" where the metrics being used might not accurately reflect value creation, be too complicated to track, or not keep pace with changing market conditions.

Oracle: Automating Task Matching and Deployment

Building upon the foundation laid by Nexus, ArcHPC Oracle takes GPU optimization to the next level. Oracle automates the complex process of task matching and deployment, eliminating the need for manual efforts that often fall short due to human limitations.

By analyzing machine code and leveraging advanced algorithms, Oracle intelligently pairs tasks to maximize GPU utilization and performance. It manages the low-level execution of instructions, making real-time adjustments to ensure optimal resource allocation. With Oracle, organizations can achieve unprecedented levels of efficiency and performance, even in large-scale, dynamic environments.

Mercury: Optimizing Hardware Selection and Scaling

ArcHPC Mercury completes the optimization triad by focusing on hardware selection and scaling. Mercury resolves task matching to maximize the number of unique tasks running concurrently, ensuring the right hardware is selected to deliver the highest throughput for the average task in the data center.

Moreover, Mercury provides valuable insights to data center owners, enabling them to make informed decisions when scaling their infrastructure to accommodate growing workloads. By optimizing hardware utilization and minimizing overprovisioning, Mercury helps organizations reduce costs and improve overall efficiency.

Real-World Impact: LAMMPS Case Study

To demonstrate the real-world impact of the ArcHPC Suite, Arc Compute showcased its performance gains in the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) case study. LAMMPS, a highly optimized code developed by renowned institutions like Sandia National Laboratories, poses significant challenges due to its high occupancy and pipeline saturation.

By leveraging Nexus alone, without the full optimization capabilities of Oracle, Arc Compute achieved a remarkable 2% performance increase on LAMMPS workloads. When running LAMMPS across multiple GPUs, the performance gains were even more substantial, with Arc Compute delivering up to 12,000 tau/day—a significant improvement over the baseline benchmarks.

The Road Ahead

As Arc Compute continues to innovate and refine its optimization techniques, the company has set ambitious milestones for the future. By the end of 2024, Arc Compute aims to release enhanced versions of Nexus and Oracle, offering features such as cross-datacenter ideal VM deployment, ISA translations between NVIDIA architectures, and support for custom scheduling systems.

With a strong focus on strategic partnerships and direct engagements with large AI/ML companies and supercomputing facilities, Arc Compute is poised to make a significant impact in the HPC landscape. The company's innovative pricing model, based on per-GPU volume pricing and cloud-based hourly rates, offers flexibility and cost-effectiveness to its customers.

Conclusion

Arc Compute's mission to maximize GPU performance and utilization while reducing hardware requirements and environmental impact is a game-changer for the AI and HPC communities. By harnessing the power of low-level optimization and intelligent task matching, Arc Compute empowers organizations to unlock the full potential of their GPU investments.

As the demand for accelerated computing continues to grow, Arc Compute stands ready to support developers, engineers, and architects in their pursuit of peak performance and efficiency. With the ArcHPC Suite, organizations can overcome the limitations of traditional solutions and achieve unprecedented levels of GPU utilization and performance.

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Opinions expressed by DZone contributors are their own.

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