ARITHMETIC PROGRESSIONS in 1 Shot: FULL CHAPTER (Theory + PYQs) | Class 10 Board | WARRIOR 2025
4:21:38
YouTubePhysics Wallah Foundation
ARITHMETIC PROGRESSIONS in 1 Shot: FULL CHAPTER (Theory + PYQs) | Class 10 Board | WARRIOR 2025
Download FREE PYQs: https://physicswallah.onelink.me/ZAZB/uazukzn8 📝 Notes: https://t.me/foundationwallah 📲 PW App/Website: https://physicswallah.onelink.me/ZAZB/PWAppWEb 📚 PW Store: https://physicswallah.onelink.me/ZAZB/vsff3zl9 ------------------------------------------------------- Learn all about arithmetic progressions in this ...
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Glitchified on Instagram: "Modern GPUs perform 10^12–10^15 arithmetic operations per second depending on class and precision. Explanation and examples: FLOPS = floating-point operations per second. 1 TFLOP = 10^12 FLOPS. Midrange/mobile GPUs: hundreds of GFLOPS to a few TFLOPS (10^9–10^12 FLOPS). High-end consumer desktop GPUs: tens of TFLOPS. Example: an RTX 4090 ≈ 82.6 TFLOPS (≈8.26×10^13 FLOPS) for FP32 peak. Data-center AI/HPC GPUs using low-precision matrix engines: hundreds to nearly a tho
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Glitchified on Instagram: "Modern GPUs perform 10^12–10^15 arithmetic operations per second depending on class and precision. Explanation and examples: FLOPS = floating-point operations per second. 1 TFLOP = 10^12 FLOPS. Midrange/mobile GPUs: hundreds of GFLOPS to a few TFLOPS (10^9–10^12 FLOPS). High-end consumer desktop GPUs: tens of TFLOPS. Example: an RTX 4090 ≈ 82.6 TFLOPS (≈8.26×10^13 FLOPS) for FP32 peak. Data-center AI/HPC GPUs using low-precision matrix engines: hundreds to nearly a tho
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