这颗芯片，还有机会吗？

Core Viewpoint - The article discusses the evolution and significance of high-performance computing (HPC) and AI accelerators, particularly focusing on Pezy Computing's advancements in mathematical accelerators that rival GPUs in performance and energy efficiency [1][2][32]. Group 1: High-Performance Computing and AI Accelerators - The global system expenditure is now dominated by AI servers filled with accelerators, with GPUs being the preferred choice due to their design for high-throughput vector processing and support for various workloads [1]. - Pezy Computing has developed a series of mathematical accelerators over 15 years, aiming to maximize energy efficiency while performing similar tasks as GPUs [2][8]. - The Pezy-SC series of accelerators has shown significant performance improvements over the years, with the latest Pezy-SC4s expected to deliver 24.9% higher floating-point throughput compared to its predecessor [7][8]. Group 2: Technical Specifications and Performance Metrics - The Pezy-SC4s chip, set to launch in 2026, will feature 2,048 cores, a clock speed of 1.5 GHz, and 96 GB of HBM3 memory with a bandwidth of 3.2 TB/s [8][30]. - The performance metrics of Pezy chips have improved significantly, with the Pezy-SC3 achieving 19.7 TFLOPS in double precision and the upcoming SC4s expected to reach 24.6 TFLOPS [4][8]. - The architecture of Pezy chips allows for efficient memory usage and high throughput, with the SC4s chip designed to support multiple precision formats including FP64, FP32, and FP16 [8][12]. Group 3: Market Position and Future Outlook - Pezy Computing's advancements position it as a competitive alternative to Nvidia GPUs, particularly in high-precision floating-point operations, which are crucial for HPC and AI workloads [30][31]. - The Japanese government’s investment in Pezy Computing is seen as a strategic move to maintain expertise in mathematical accelerator design, ensuring a backup option in case of GPU supply constraints [32]. - The anticipated performance of the Pezy-SC4 in genomic analysis tasks suggests it could outperform Nvidia's H100 GPUs, indicating a strong potential for market adoption [29][30].