{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [], "name": "Terabyte_L1_Cache_Monte_Carlo_Simulation.ipynb", "gpuType": "L4", "authorship_tag": "ABX9TyN61V7XvwLRjii2ZmpwGhC5", "include_colab_link": true }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" }, "accelerator": "GPU" }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "source": [ "Monte Carlo simulation of a trend towards achieving terabyte (TB) level L1 cache memory. See below for gigabyte level L1 cache memory." ], "metadata": { "id": "BCstvk1WraL8" } }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "Ry6i0ZQ1rY8m", "outputId": "fd8f0608-0537-4c72-82cb-f4a6e1e954f9" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Simulation runs: 10000\n", "Required Doublings to 1TB from 64KB: 24\n", "Mean Years to Achieve: 60.2\n", "Median Years to Achieve: 60.2\n", "Min/Max Years to Achieve: 43.1/74.5\n", "Mean Finish Year (starting 2025): ~2085\n", "Median Finish Year (starting 2025): ~2085\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ], "source": [ "import numpy as np\n", "import statistics\n", "import matplotlib.pyplot as plt\n", "\n", "# Onri prefers using rcParams to increase the quality of all plots to be higher than the default settings.\n", "# This only needs to be done once at beginning of every Jupyter Notebook.\n", "plt.rcParams['figure.dpi'] = 200\n", "\n", "# --- Simulation Parameters ---\n", "NUM_SIMULATIONS = 10_000\n", "DOUBLINGS_REQUIRED = 24\n", "\n", "# Mean and std dev for the doubling interval (in years):\n", "MEAN_DOUBLING_TIME = 2.5\n", "STD_DOUBLING_TIME = 0.75\n", "\n", "# We'll clamp doubling times to [0.5, 10] years as a sanity check\n", "MIN_DOUBLING = 0.5\n", "MAX_DOUBLING = 10.0\n", "\n", "# Optional: define a small probability of \"breakthrough\" or \"stall\"\n", "# that modifies the doubling time distribution. We'll keep it off for now\n", "BREAKTHROUGH_CHANCE = 0.0\n", "STALL_CHANCE = 0.0\n", "\n", "def random_doubling_time():\n", " \"\"\"\n", " Returns a random doubling time drawn from a truncated normal distribution.\n", " Could incorporate special 'breakthrough' or 'stall' events.\n", " \"\"\"\n", " while True:\n", " time = np.random.normal(MEAN_DOUBLING_TIME, STD_DOUBLING_TIME)\n", " # Clamp to a reasonable range\n", " if time > MIN_DOUBLING and time < MAX_DOUBLING:\n", " break\n", "\n", " # Optionally incorporate random breakthroughs or stalls\n", " # if np.random.rand() < BREAKTHROUGH_CHANCE:\n", " # time *= 0.5 # Halve the time needed for a doubling\n", " # if np.random.rand() < STALL_CHANCE:\n", " # time *= 2.0 # Double the time needed for a doubling\n", "\n", " return time\n", "\n", "def simulate_one_run():\n", " \"\"\"\n", " Sums random doubling intervals until we reach the required number of doublings.\n", " Returns the total time in years.\n", " \"\"\"\n", " total_time = 0.0\n", " doublings_done = 0\n", "\n", " # Keep adding doubling intervals until we hit DOUBLINGS_REQUIRED\n", " while doublings_done < DOUBLINGS_REQUIRED:\n", " total_time += random_doubling_time()\n", " doublings_done += 1\n", "\n", " return total_time\n", "\n", "# --- Monte Carlo Simulation ---\n", "results = [simulate_one_run() for _ in range(NUM_SIMULATIONS)]\n", "\n", "# Analyze results\n", "mean_years = statistics.mean(results)\n", "median_years = statistics.median(results)\n", "min_years = min(results)\n", "max_years = max(results)\n", "\n", "# Let's imagine we start counting from 2025\n", "start_year = 2025\n", "mean_finish_year = start_year + mean_years\n", "median_finish_year = start_year + median_years\n", "\n", "# Print out some summary statistics\n", "print(f\"Simulation runs: {NUM_SIMULATIONS}\")\n", "print(f\"Required Doublings to 1TB from 64KB: {DOUBLINGS_REQUIRED}\")\n", "print(f\"Mean Years to Achieve: {mean_years:.1f}\")\n", "print(f\"Median Years to Achieve: {median_years:.1f}\")\n", "print(f\"Min/Max Years to Achieve: {min_years:.1f}/{max_years:.1f}\")\n", "print(f\"Mean Finish Year (starting 2025): ~{mean_finish_year:.0f}\")\n", "print(f\"Median Finish Year (starting 2025): ~{median_finish_year:.0f}\")\n", "\n", "# Plot the distribution\n", "plt.hist(results, bins=50, color='skyblue', edgecolor='black')\n", "plt.title(\"Distribution of Years Required to Reach 1TB L1 (Monte Carlo)\")\n", "plt.xlabel(\"Years to Achieve (from 2025)\")\n", "plt.ylabel(\"Frequency\")\n", "plt.show()\n" ] }, { "cell_type": "code", "source": [ "# If you haven’t already installed CuPy, uncomment and run one of these lines:\n", "# (Choose the one that matches your Colab’s CUDA version. 11.x is most common.)\n", "# !pip install cupy-cuda11x --quiet\n", "# !pip install cupy-cuda11.0 --quiet\n", "# !pip install cupy-cuda11.1 --quiet\n", "# !pip install cupy-cuda11.2 --quiet\n", "# !pip install cupy-cuda11.3 --quiet\n", "# !pip install cupy-cuda11.4 --quiet\n", "# !pip install cupy-cuda11.5 --quiet\n", "\n", "import numpy as np\n", "import cupy as cp\n", "import statistics\n", "import matplotlib.pyplot as plt\n", "import time\n", "\n", "# Increase plot DPI\n", "plt.rcParams['figure.dpi'] = 200\n", "\n", "# --- Simulation Parameters ---\n", "NUM_SIMULATIONS = 10_000\n", "DOUBLINGS_REQUIRED = 24\n", "\n", "MEAN_DOUBLING_TIME = 2.5\n", "STD_DOUBLING_TIME = 0.75\n", "MIN_DOUBLING = 0.5\n", "MAX_DOUBLING = 10.0\n", "\n", "# --- Helper for CPU (pure Python/NumPy) ---\n", "def random_doubling_time_cpu():\n", " while True:\n", " t = np.random.normal(MEAN_DOUBLING_TIME, STD_DOUBLING_TIME)\n", " if MIN_DOUBLING < t < MAX_DOUBLING:\n", " return t\n", "\n", "def simulate_one_run_cpu():\n", " total = 0.0\n", " count = 0\n", " while count < DOUBLINGS_REQUIRED:\n", " total += random_doubling_time_cpu()\n", " count += 1\n", " return total\n", "\n", "# --- Run on CPU ---\n", "start_cpu = time.time()\n", "results_cpu = [simulate_one_run_cpu() for _ in range(NUM_SIMULATIONS)]\n", "end_cpu = time.time()\n", "time_cpu = end_cpu - start_cpu\n", "\n", "# --- Run on GPU via CuPy ---\n", "# We can vectorize the “generate 24 truncated‐normal draws per simulation, then sum”.\n", "# Steps:\n", "# 1. Generate an array of shape (NUM_SIMULATIONS, DOUBLINGS_REQUIRED) of standard normals.\n", "# 2. Scale and shift by (STD_DOUBLING_TIME, MEAN_DOUBLING_TIME).\n", "# 3. Clamp to [MIN_DOUBLING, MAX_DOUBLING].\n", "# 4. Sum each row (axis=1) to get one “total_time” per simulation.\n", "# 5. Copy back to host for statistics/plotting.\n", "\n", "# Move all random draws and summation onto GPU\n", "cp.random.seed(42) # for reproducibility\n", "\n", "# Warm-up allocation (optional)\n", "_d = cp.arange(1) # touch the GPU once\n", "\n", "start_gpu = time.time()\n", "# 1) Draw standard normals of shape (NUM_SIMULATIONS, DOUBLINGS_REQUIRED)\n", "gauss = cp.random.standard_normal(size=(NUM_SIMULATIONS, DOUBLINGS_REQUIRED), dtype=cp.float32)\n", "\n", "# 2) Scale & shift\n", "scaled = gauss * STD_DOUBLING_TIME + MEAN_DOUBLING_TIME\n", "\n", "# 3) Clamp\n", "clamped = cp.clip(scaled, MIN_DOUBLING, MAX_DOUBLING)\n", "\n", "# 4) Sum each row → total time per simulation\n", "results_gpu = clamped.sum(axis=1)\n", "\n", "# 5) Copy back to host (NumPy array)\n", "results_gpu_host = cp.asnumpy(results_gpu)\n", "cp.cuda.Stream.null.synchronize()\n", "end_gpu = time.time()\n", "time_gpu = end_gpu - start_gpu\n", "\n", "# --- Compare statistics ---\n", "# CPU stats\n", "mean_cpu = statistics.mean(results_cpu)\n", "median_cpu = statistics.median(results_cpu)\n", "min_cpu = min(results_cpu)\n", "max_cpu = max(results_cpu)\n", "\n", "# GPU stats (from results_gpu_host)\n", "mean_gpu = float(np.mean(results_gpu_host))\n", "median_gpu = float(np.median(results_gpu_host))\n", "min_gpu = float(np.min(results_gpu_host))\n", "max_gpu = float(np.max(results_gpu_host))\n", "\n", "print(f\"CPU time : {time_cpu:.3f} s for {NUM_SIMULATIONS} sims\")\n", "print(f\"GPU time : {time_gpu:.3f} s for {NUM_SIMULATIONS} sims (CuPy)\")\n", "print(\"--- Result Comparison (CPU vs GPU) ---\")\n", "print(f\"Mean → CPU: {mean_cpu:.3f} | GPU: {mean_gpu:.3f}\")\n", "print(f\"Median → CPU: {median_cpu:.3f} | GPU: {median_gpu:.3f}\")\n", "print(f\"Min/Max→ CPU: {min_cpu:.3f}/{max_cpu:.3f} | GPU: {min_gpu:.3f}/{max_gpu:.3f}\")\n", "\n", "# --- Plot distributions ---\n", "fig, ax = plt.subplots()\n", "ax.hist(results_cpu, bins=50, color='lightgreen', edgecolor='black')\n", "ax.set_title(\"CPU: Distribution of Years to Reach 1 TB (Monte Carlo)\")\n", "ax.set_xlabel(\"Years (from 2025)\")\n", "ax.set_ylabel(\"Frequency\")\n", "plt.show()\n", "\n", "fig, ax = plt.subplots()\n", "ax.hist(results_gpu_host, bins=50, color='skyblue', edgecolor='black')\n", "ax.set_title(\"GPU (CuPy): Distribution of Years to Reach 1 TB (Monte Carlo)\")\n", "ax.set_xlabel(\"Years (from 2025)\")\n", "ax.set_ylabel(\"Frequency\")\n", "plt.show()" ], "metadata": { "id": "oQgV75F6VsEk", "outputId": "c242a22e-78ed-4d65-8b13-044bc0e3e6e9", "colab": { "base_uri": "https://localhost:8080/", "height": 1000 } }, "execution_count": 5, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "CPU time : 0.238 s for 10000 sims\n", "GPU time : 0.431 s for 10000 sims (CuPy)\n", "--- Result Comparison (CPU vs GPU) ---\n", "Mean → CPU: 60.226 | GPU: 60.066\n", "Median → CPU: 60.218 | GPU: 60.067\n", "Min/Max→ CPU: 47.848/74.939 | GPU: 45.384/75.656\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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CQ0PTXE9ISIgLWgMAAACkXYaGO3Hy5MmjZs2aZXQzAADZQGhoqIKDgzO6GQAAAIDLZIpwBwAAd7N52ORf1D/V298IueHC1gAAAACpR7gDAMiW/Iv6a9zhcane/o1Cb8iIMVzYIgAAACB13B7uvPzyy6ne1mazac6cOS5sDQAAAAAAgLW5PdyZP3++Oe15ShiGQbgDAAAAAABwH7eHO2XKlEk23Ll9+7auXLliBjqFChWSn5+fm1oIAAAAAABgHW4Pd06fPu1UuWvXrmnx4sUaPXq08uXLpx9++EFVq1ZN38YBAAAAAABYjEdGNyAx+fPn14ABA7Rjxw5dvHhRbdq00bVr1zK6WQAAAAAAAJlKpg134lStWlWDBw/W6dOn9fnnn2d0cwAAAAAAADKVTB/uSFLr1q0lSStWrMjglgAAAAAAAGQulgh3cufOLUk6c+ZMBrcEAAAAAAAgc7FEuLNv3z5JUo4cOTK4JQAAAAAAAJlLpg93Tp06pbFjx8pms+nhhx92SZ1hYWH67rvv9J///EfNmzdXpUqVlDdvXnl7e6tIkSJ67LHH9Omnn+rKlStO1ff777/rhRdeUNmyZeXr66tixYrpySef1OLFi1PUrsWLF+uJJ55QsWLF5Ovrq7Jly+qFF17Qzp07U3OYAAAAAAAgG3D7VOgLFy5MtkxMTIyuXbumwMBArV69WuHh4bLZbHr11Vdd0oY9e/aoR48eCa67dOmStmzZoi1btmjChAn65ptv9OSTTyZa19ixY/X+++8rJibGvO/ChQv65Zdf9Msvv+jbb7/V999/L19f30TriIiIUJcuXfTTTz853H/mzBl9++235pTwY8aMSeGRAgAAAACArM7t4U6vXr1ks9mcLm8YhiRp8ODB6t69u8vaUbp0abVo0UKPPvqoSpcureLFiysmJkbnzp3T999/rxUrVujy5ctq37699uzZo1q1asWr46uvvtK4ceMkSRUrVtR///tf1axZU+fPn9f//vc/bdq0SWvXrtXLL7+sRYsWJdqWl19+2Qx2WrRooSFDhqhEiRI6ePCgPvroI508eVJjx45V8eLF1b9/f5c9BgAAAAAAwPrcHu5I/xfYJCdfvnxq1qyZBgwYoCeeeMJl+2/RokWSgzN369ZNq1atUkBAgCIjIzVu3Lh4M3VdvXpVw4cPlySVKVNGu3btUqFChcz1zzzzjAICArRmzRotXrxY/fv312OPPRZvXxs3btR3330nSWrXrp1WrlwpT09PSVLdunXVvn17Pfroozpz5oyGDx+url27Kn/+/Gl9CAAAAAAAQBbh9nDn1KlTyZbx8PBQnjx5lC9fvnRpQ1x4kpSOHTuqatWqOn78uLZt2xZv/ezZs3Xjxg1J0vjx4x2Cnbh9fPnll/rpp58UHR2tCRMmJBjufPbZZ5IkLy8vffnll/HaVqhQIY0fP149evTQ9evXNXv2bL399tvOHioAAAAAAMji3B7ulC1b1t27TLU8efJIku7cuRNv3apVqyRJ/v7+6tSpU4LblypVSq1bt9b69eu1YcMG3bx506xTkm7evKkNGzZIklq3bq1SpUolWE+nTp3k7++vsLAwrVy5knAHAAAAAACYMv1sWRnl+PHj2r9/vySpWrVqDusiIyO1Z88eSVLDhg3l7e2daD3NmzeXJN29e1eBgYEO6/bu3avIyEiHcgnx9vZWgwYNzG3u3buXsoMBAAAAAABZFuGOnfDwcP3999/64osv1Lx5c0VFRUmShg4d6lAuKChI0dHRkuIHP/ezX3/06FGHdUeOHEmwXFL1REVF6e+//076QAAAAAAAQLaRIQMqZybz589X7969E10/YsQIPffccw73nTt3zlxO7FKqOKVLlzaXz54967J6qlevnmT5+9nvKyEhISEpqg8AAAAAAGQObg93nBnMOKVsNpvZy8ZVHn74Yc2cOVN169aNt+7mzZvmcu7cuZOsJ1euXObyrVu30qUeZ9iHQwAAAAAAIOtwe7jj7DTo7tKxY0fVqVNHkhQREaGTJ09q6dKlWrlypXr06KFJkybpmWeecdjGfoDlpMbbkSQfHx9zOSIiIl3qAQAAAAAA2Zfbw50xY8ZIktauXWsOMFyjRg3Vq1dPRYsWlSRduHBBe/fu1aFDh2Sz2VSnTh21bds2XdqTL18+hynX69atq2effVZff/21evbsqQ4dOmjOnDnq1auXWcbX19dcjhsQOTF37941l3PmzOmwzlX1OOP+S8LuFxISonr16qW4XgAAAAAAkLEyJNx57733FBgYqFq1aiV66ZMUOzPUK6+8osDAQD399NMaPXq029r54osv6scff9TSpUs1cOBAtW/fXgUKFJAkh+nMk7tE6vbt2+by/ZdeuaoeZyQ3pg8AAAAAALAmt8+WtWHDBo0dO1ZVqlTR9u3bEw12pNheNNu2bVOlSpU0btw4/fbbb25sqdShQwdJscHKzz//bN5vH5QkN1CxfY+Z+8e9cVU9AAAAAAAg+3J7uDN58mTZbDaNGDHCYZDgxOTKlUsjRoyQYRiaMmWKG1r4fwoXLmwu//vvv+ZylSpVzIGhjx07lmQd9usfeOABh3X2M145W4+Xl5cqV66cTMsBAAAAAEB24fZwJ26cnYceesjpbWrVqiUp9jItdwoODjaX7S+F8vb2Nsen2blzZ5Lj5WzZskVS7IDIcQM3x6lbt645kHJcuYRERkZq165d5jY5cuRI4ZEAAAAAAICsyu3hztWrVyVJN27ccHqbsLAwSdK1a9fSpU2JWbZsmblcs2ZNh3UdO3aUFNu2FStWJLj9uXPnzEvJWrVq5TDGjhQ75k6rVq0kSb/99luil2atWLHCfAwCAgJSfiAAAAAAACDLcnu4U6JECUnS8uXLnd7m+++/lyQVL17cJW2YP3++wzTkCZk4caJ++uknSVL58uXVtGlTh/V9+/ZV3rx5JUkjRozQlStXHNZHR0drwIABio6OliS9/fbbCe7nrbfekiRFRUXp9ddfN8vHuXz5soYPHy4pdmavvn37OnOIAAAAAAAgm3B7uPPUU0/JMAx99dVXWrp0abLlv//+e3311Vey2Wwumw597NixKlmypPr376+FCxdqx44dOnDggLZv367p06erSZMmevPNNyXFXoI1c+ZMc4ydOAUKFND48eMlxY7HU79+fc2bN0+BgYH64Ycf9Pjjj2vNmjWSpB49euixxx5LsC0tW7bUs88+K0nmdj/88IMCAwM1b948NWjQQGfOnJEkjR8/Xvnz53fJYwAAAAAAALIGt0+F/t///lfffvutbt68qR49emjRokXq1auX6tatqyJFishms+nChQvau3evFixYoB9++EGGYcjf318jR450WTuuXr2qWbNmadasWYmWKVWqlObOnavWrVsnuP6VV17R+fPn9f777+vkyZN6+eWX45Vp27at5s6dm2Rb5s6dq7CwMP3000/atGmTNm3a5LDew8NDo0aNUv/+/Z04MgAAAAAAkJ24PdwpWbKk1qxZo3bt2iksLExr1qwxe7gkxDAM5cmTR6tXr1bJkiVd0ob169dr7dq12rFjh06cOKELFy7oypUrypkzp4oUKaKHH35YzzzzjLp16yY/P78k6xo3bpyefPJJTZs2Tdu2bdOFCxeUL18+1apVS71791aPHj2SbU/OnDm1du1aLVq0SPPnz9eBAwd0/fp1FS1aVE2bNtXAgQPVsGFDlxw7AAAAAADIWtwe7khS06ZNdfDgQb355ptatWpVvHFm4nh6eqpDhw76/PPPVbZsWZftv2rVqqpatap56VVaNWrUSI0aNUpzPc8995yee+45F7QIAAAAAABkFxkS7khS6dKltWzZMl24cEGbNm3SwYMHzZm08ufPr5o1a6pFixYqVqxYRjURAAAAAAAg08uwcCdO0aJF9eyzz5qDCgMAAAAAAMB5bp8tCwAAAAAAAK6T4T13IiIi9Mcffyg0NFTh4eHq2LGj/P39M7pZAAAAAAAAlpBh4c7Zs2f13//+V8uWLdO9e/fM++vUqaPq1aubt+fMmaOvvvpKefPm1S+//CKbzZYRzQUAZLA6deooNDQ0zfWEhIS4oDUAAABA5pEh4c7u3bv19NNP69q1azIMw7w/oeCmXbt2ev3113Xv3j398ssvevLJJ93ZVABAJhEaGqrg4OCMbgYAAACQ6bg93Ll+/bo6dOigq1evqnjx4ho1apSaNm2qmjVrJli+SJEiatOmjX744QetXbuWcAcAsjmbh03+RVN/+e6NkBsubA0AAACQ8dwe7kyePFkXL15UoUKFtHPnTpUpUybZbVq3bq3Vq1drz549bmghACAz8y/qr3GHx6V6+zcKvSEjxki+IAAAAGARbp8ta82aNbLZbHrzzTedCnYkqUaNGpKkkydPpmfTAAAAAAAALMft4c6JEyckSc2aNXN6m/z580uSwsLC0qVNAAAAAAAAVuX2cOfOnTuSpBw5cji9ze3btyVJOXPmTJc2AQAAAAAAWJXbw50iRYpIkk6dOuX0Nvv375cklShRIj2aBAAAAAAAYFluD3fq168vSVq3bp1T5Q3D0KxZs2Sz2dS0adP0bBoAAAAAAIDluD3cef7552UYhr799luzR05S/vOf/+jAgQOSpJ49e6Zz6wAAAAAAAKzF7eFOhw4d1KJFC0VFRalVq1aaPn26Ll68aK6PiorS+fPntWzZMjVt2lT/+9//ZLPZ1KlTJzVq1MjdzQUAAAAAAMjUvDJip8uXL1erVq20b98+DRw4UAMHDpTNZpMk1a5d26GsYRhq0KCB5s+fnwEtBQAAAAAAyNzc3nNHkvLly6edO3dq5MiR8vf3l2EYCf7LmTOnhg0bps2bNytXrlwZ0VQAAAAAAIBMLUN67kiSt7e3PvzwQ/33v//Vli1bFBgYqIsXLyo6OloFCxZU7dq11bp1a+XNmzejmggAAAAAAJDpuT3cWbhwoSSpatWqql+/vnLlyqW2bduqbdu27m4KAAAAAACA5bn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\n" 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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "import pandas as pd\n", "\n", "# References supporting the exponential growth in cache memory capacity\n", "references_data = [\n", " {\n", " \"Reference\": \"Hennessy & Patterson, Computer Architecture: A Quantitative Approach\",\n", " \"Year\": 2017,\n", " \"Note\": \"Discussion on exponential trends in cache and memory scaling.\"\n", " },\n", " {\n", " \"Reference\": \"International Technology Roadmap for Semiconductors (ITRS)\",\n", " \"Year\": 2015,\n", " \"Note\": \"Predictions of semiconductor technology scaling, including cache memory sizes.\"\n", " },\n", " {\n", " \"Reference\": \"Samuel K. Moore, IEEE Spectrum: 'Chipmakers Push SRAM Density for Next-Gen Caches'\",\n", " \"Year\": 2022,\n", " \"Note\": \"Recent advancements and breakthroughs in SRAM cache density.\"\n", " },\n", " {\n", " \"Reference\": \"T. Naffziger, IEEE ISSCC Keynote: 'Future of Processor Scaling'\",\n", " \"Year\": 2023,\n", " \"Note\": \"Insights into future scaling of processor caches reaching gigabyte and terabyte scales.\"\n", " },\n", " {\n", " \"Reference\": \"AMD Technical Roadmap Presentation\",\n", " \"Year\": 2024,\n", " \"Note\": \"Projected exponential growth in processor caches to multi-gigabyte and eventually terabyte levels.\"\n", " }\n", "]\n", "\n", "# Creating a DataFrame to neatly display the references\n", "df_references = pd.DataFrame(references_data)\n", "display(df_references)" ], "metadata": { "id": "TGi8_Srm1mBW", "outputId": "7311f3aa-8179-4224-802a-d69d623c11d2", "colab": { "base_uri": "https://localhost:8080/", "height": 206 } }, "execution_count": 6, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ " Reference Year \\\n", "0 Hennessy & Patterson, Computer Architecture: A... 2017 \n", "1 International Technology Roadmap for Semicondu... 2015 \n", "2 Samuel K. Moore, IEEE Spectrum: 'Chipmakers Pu... 2022 \n", "3 T. Naffziger, IEEE ISSCC Keynote: 'Future of P... 2023 \n", "4 AMD Technical Roadmap Presentation 2024 \n", "\n", " Note \n", "0 Discussion on exponential trends in cache and ... \n", "1 Predictions of semiconductor technology scalin... \n", "2 Recent advancements and breakthroughs in SRAM ... \n", "3 Insights into future scaling of processor cach... \n", "4 Projected exponential growth in processor cach... " ], "text/html": [ "\n", "
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ReferenceYearNote
0Hennessy & Patterson, Computer Architecture: A...2017Discussion on exponential trends in cache and ...
1International Technology Roadmap for Semicondu...2015Predictions of semiconductor technology scalin...
2Samuel K. Moore, IEEE Spectrum: 'Chipmakers Pu...2022Recent advancements and breakthroughs in SRAM ...
3T. Naffziger, IEEE ISSCC Keynote: 'Future of P...2023Insights into future scaling of processor cach...
4AMD Technical Roadmap Presentation2024Projected exponential growth in processor cach...
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df_references", "summary": "{\n \"name\": \"df_references\",\n \"rows\": 5,\n \"fields\": [\n {\n \"column\": \"Reference\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"International Technology Roadmap for Semiconductors (ITRS)\",\n \"AMD Technical Roadmap Presentation\",\n \"Samuel K. Moore, IEEE Spectrum: 'Chipmakers Push SRAM Density for Next-Gen Caches'\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Year\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3,\n \"min\": 2015,\n \"max\": 2024,\n \"num_unique_values\": 5,\n \"samples\": [\n 2015,\n 2024,\n 2022\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Note\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"Predictions of semiconductor technology scaling, including cache memory sizes.\",\n \"Projected exponential growth in processor caches to multi-gigabyte and eventually terabyte levels.\",\n \"Recent advancements and breakthroughs in SRAM cache density.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {} } ] }, { "source": [ "# @title Year\n", "\n", "from matplotlib import pyplot as plt\n", "df_references['Year'].plot(kind='line', figsize=(8, 4), title='Year')\n", "plt.gca().spines[['top', 'right']].set_visible(False)" ], "cell_type": "code", "execution_count": null, "outputs": [], "metadata": { "id": "Uy-SCxR0WSMN" } }, { "cell_type": "markdown", "source": [ "Below is a Lowess fitting curve applied to the data" ], "metadata": { "id": "ooiYKpvpsNzf" } }, { "cell_type": "code", "source": [ "# GPU‐Accelerated Sorting + LOWESS Example (CuPy + statsmodels)\n", "# ==============================================================\n", "# Below is a demonstration of how to use CUDA‐accelerated array operations\n", "# (via CuPy) together with statsmodels' LOWESS (which runs on CPU).\n", "# ----------------------------------------------------------------\n", "# NOTE: statsmodels.lowess itself does NOT natively run on GPU. However,\n", "# you can:\n", "# 1. Move data to the GPU for sorting/array arithmetic (with CuPy).\n", "# 2. Copy sorted data back to host (NumPy) and apply statsmodels.lowess.\n", "# ----------------------------------------------------------------\n", "\n", "import numpy as np\n", "import cupy as cp\n", "import matplotlib.pyplot as plt\n", "from statsmodels.nonparametric.smoothers_lowess import lowess\n", "import time\n", "\n", "# Assume `results` is a NumPy array of length NUM_SIMULATIONS.\n", "# For demonstration, generate synthetic `results` on the host:\n", "NUM_SIMULATIONS = 10_000\n", "np.random.seed(0)\n", "results = np.random.normal(loc=50, scale=10, size=NUM_SIMULATIONS)\n", "\n", "# -----------------------\n", "# 1) GPU: Transfer + Sort\n", "# -----------------------\n", "# Move `results` to GPU\n", "start_gpu_sort = time.time()\n", "gpu_results = cp.asarray(results, dtype=cp.float32)\n", "\n", "# Perform sorting on the GPU\n", "gpu_sorted = cp.sort(gpu_results)\n", "cp.cuda.Stream.null.synchronize() # ensure completion\n", "gpu_sort_time = time.time() - start_gpu_sort\n", "\n", "# Copy sorted results back to host (NumPy)\n", "sorted_results_gpu = cp.asnumpy(gpu_sorted)\n", "\n", "# ---------------------------\n", "# 2) CPU: Apply statsmodels LOWESS\n", "# ---------------------------\n", "# Create x-axis for sorted indices (NumPy)\n", "x = np.arange(NUM_SIMULATIONS)\n", "\n", "# Run LOWESS smoothing: CPU only\n", "start_cpu_lowess = time.time()\n", "# frac=0.05 => 5% of points used for each local regression\n", "smoothed = lowess(sorted_results_gpu, x, frac=0.05)\n", "x_smooth = smoothed[:, 0]\n", "y_smooth = smoothed[:, 1]\n", "cpu_lowess_time = time.time() - start_cpu_lowess\n", "\n", "# ---------------------------\n", "# 3) Plot & Print Timings\n", "# ---------------------------\n", "print(f\"GPU sorting time: {gpu_sort_time:.4f} s\")\n", "print(f\"CPU LOWESS time: {cpu_lowess_time:.4f} s\")\n", "\n", "# Plot original sorted + smoothed curve:\n", "plt.figure(figsize=(10, 6))\n", "plt.plot(x, sorted_results_gpu, label='Sorted (CuPy→NumPy)', alpha=0.3)\n", "plt.plot(x_smooth, y_smooth, color='red', linewidth=2.0, label='LOWESS Smoothed (CPU)')\n", "plt.title(\"GPU‐Sorted + CPU‐Smoothed Distribution\")\n", "plt.xlabel(\"Simulation Index (sorted)\")\n", "plt.ylabel(\"Value\")\n", "plt.legend()\n", "plt.show()\n", "\n", "# -----------------------------------------------------\n", "# 4) Alternative: Fully‐GPU LOWESS Approximation (optional)\n", "# -----------------------------------------------------\n", "# If you need a GPU‐only smoothing step, you must implement\n", "# a custom CUDA kernel or use a GPU‐accelerated library such as\n", "# RAPIDS cuDF / cuML (e.g., cuML's KNN or other regressor) to\n", "# approximate a LOWESS‐like curve. That approach is beyond the\n", "# built‐in statsmodels.lowess function, but here's a sketch:\n", "#\n", "# from cuml.neighbors import NearestNeighbors\n", "# from cuml.linear_model import LinearRegression\n", "#\n", "# 1) Keep `gpu_sorted` on GPU (shape (N,)).\n", "# 2) Create a GPU array of indices: gpu_x = cp.arange(N, dtype=cp.float32)\n", "# 3) For each index i, select a local window of (frac*N) neighbors\n", "# using cuML's NearestNeighbors, perform a weighted linear fit,\n", "# and store fitted y_i in `gpu_y_smooth`. This replicates LOWESS.\n", "# 4) Plot `gpu_y_smooth` (after copying to host) similarly.\n", "#\n", "# The cuML approach requires a more detailed setup and is not a one‐line drop‐in.\n", "# For most cases, combining CuPy sorting with statsmodels.lowess (on CPU)\n", "# is simpler unless your dataset is extremely large, in which case\n", "# implementing a fully‐GPU smoothing is recommended." ], "metadata": { "id": "PiyRYfe5WvBF", "outputId": "cb9afeda-25d6-4152-dc28-e0efcefd990d", "colab": { "base_uri": "https://localhost:8080/", "height": 976 } }, "execution_count": 9, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "GPU sorting time: 0.1685 s\n", "CPU LOWESS time: 1.1151 s\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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}, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "Below is a moving average fitting curve applied to the data" ], "metadata": { "id": "hqjngBedvjL4" } }, { "cell_type": "code", "source": [ "# GPU-Accelerated Rolling Mean (CuPy) for Sorted Results\n", "# ==========================================================\n", "# This cell demonstrates how to compute the moving average (rolling mean) on the GPU\n", "# using CuPy, then bring the result back to NumPy for plotting.\n", "# -------------------------------------------------------------------------------\n", "\n", "import numpy as np\n", "import cupy as cp\n", "import matplotlib.pyplot as plt\n", "import time\n", "\n", "# --- Example Setup: Simulated 'sorted_results' on CPU ---\n", "# (In your notebook, `sorted_results` would come from your Monte Carlo simulation.)\n", "NUM_SIMULATIONS = 10_000\n", "np.random.seed(0)\n", "results = np.random.normal(loc=50, scale=10, size=NUM_SIMULATIONS)\n", "sorted_results = np.sort(results)\n", "\n", "# --- Rolling Mean Parameters ---\n", "window_size = 200\n", "\n", "# ------------------------\n", "# 1) GPU: Compute Rolling Mean\n", "# ------------------------\n", "start_gpu = time.time()\n", "# Transfer to GPU\n", "gpu_sorted = cp.asarray(sorted_results, dtype=cp.float32)\n", "\n", "# Create the convolution kernel (all ones / window_size)\n", "kernel = cp.ones(window_size, dtype=cp.float32) / window_size\n", "\n", "# Perform 1D convolution in 'valid' mode to get rolling means\n", "gpu_rolling = cp.convolve(gpu_sorted, kernel, mode='valid')\n", "cp.cuda.Stream.null.synchronize()\n", "gpu_time = time.time() - start_gpu\n", "\n", "# Copy rolling mean results back to host\n", "rolling_means_gpu = cp.asnumpy(gpu_rolling)\n", "\n", "# -------------------------\n", "# 2) (Optional) CPU: For comparison only\n", "# -------------------------\n", "start_cpu = time.time()\n", "rolling_means_cpu = np.convolve(sorted_results, np.ones(window_size)/window_size, mode='valid')\n", "cpu_time = time.time() - start_cpu\n", "\n", "# -------------------------\n", "# 3) Print Timing Comparison\n", "# -------------------------\n", "print(f\"GPU rolling mean time: {gpu_time:.4f} s\")\n", "print(f\"CPU rolling mean time: {cpu_time:.4f} s\")\n", "\n", "# -------------------------\n", "# 4) Plot Results\n", "# -------------------------\n", "plt.figure(figsize=(10, 6))\n", "# Plot raw sorted data (semi-transparent)\n", "plt.plot(sorted_results, alpha=0.3, label='Sorted Results')\n", "\n", "# Plot GPU-derived rolling mean (offset index by window_size//2 to align)\n", "x_indices = np.arange(window_size//2, window_size//2 + len(rolling_means_gpu))\n", "plt.plot(x_indices,\n", " rolling_means_gpu,\n", " color='orange',\n", " label=f'{window_size}-Sample Rolling Mean (GPU)')\n", "\n", "# (Optional) Plot CPU-derived rolling mean for visual check\n", "tR = np.arange(window_size//2, window_size//2 + len(rolling_means_cpu))\n", "plt.plot(tR,\n", " rolling_means_cpu,\n", " color='green',\n", " linestyle='--',\n", " label=f'{window_size}-Sample Rolling Mean (CPU)',\n", " alpha=0.6)\n", "\n", "plt.title(\"Monte Carlo Distribution + GPU Rolling Mean\")\n", "plt.xlabel(\"Simulation Index (sorted by years)\")\n", "plt.ylabel(\"Years to Achieve (Ascending)\")\n", "plt.legend()\n", "plt.show()" ], "metadata": { "id": "Te8WL6VaW_LH", "outputId": "37d1cae6-9a69-447e-9a06-82439b898820", "colab": { "base_uri": "https://localhost:8080/", "height": 976 } }, "execution_count": 11, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "GPU rolling mean time: 0.8452 s\n", "CPU rolling mean time: 0.0007 s\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "Monte Carlo simulation of a trend towards achieving gigabyte level L1 cache memory." ], "metadata": { "id": "B053UBN7wrkH" } }, { "cell_type": "code", "source": [ "# If you need CuPy, uncomment one of these matching your CUDA version:\n", "# !pip install cupy-cuda11x --quiet\n", "# !pip install cupy-cuda11.0 --quiet\n", "\n", "import numpy as np\n", "import cupy as cp\n", "import statistics\n", "import matplotlib.pyplot as plt\n", "import time\n", "from statsmodels.nonparametric.smoothers_lowess import lowess\n", "\n", "# Increase plot DPI for better quality\n", "plt.rcParams['figure.dpi'] = 200\n", "\n", "# --- Simulation Parameters ---\n", "NUM_SIMULATIONS = 10_000 # Number of Monte Carlo runs\n", "DOUBLINGS_REQUIRED = 14 # ~14 doublings: 64 KB -> 1 GB\n", "MEAN_DOUBLING_TIME = 2.5 # Mean years per density doubling\n", "STD_DOUBLING_TIME = 0.75 # Std dev for years per doubling\n", "MIN_DOUBLING = 0.5 # Minimum clamped years per doubling\n", "MAX_DOUBLING = 10.0 # Maximum clamped years per doubling\n", "\n", "# --- Helper: CPU Monte Carlo ---\n", "def random_doubling_time_cpu():\n", " while True:\n", " t = np.random.normal(MEAN_DOUBLING_TIME, STD_DOUBLING_TIME)\n", " if MIN_DOUBLING < t < MAX_DOUBLING:\n", " return t\n", "\n", "\n", "def simulate_one_run_cpu():\n", " total = 0.0\n", " count = 0\n", " while count < DOUBLINGS_REQUIRED:\n", " total += random_doubling_time_cpu()\n", " count += 1\n", " return total\n", "\n", "# --- Run CPU Simulation ---\n", "start_cpu = time.time()\n", "results_cpu = [simulate_one_run_cpu() for _ in range(NUM_SIMULATIONS)]\n", "end_cpu = time.time()\n", "cpu_time = end_cpu - start_cpu\n", "\n", "# Compute CPU statistics\\mean_cpu = statistics.mean(results_cpu)\n", "median_cpu = statistics.median(results_cpu)\n", "min_cpu = min(results_cpu)\n", "max_cpu = max(results_cpu)\n", "\n", "print(f\"CPU: {cpu_time:.3f} s for {NUM_SIMULATIONS} sims\")\n", "print(f\"Mean (CPU): {mean_cpu:.2f}, Median (CPU): {median_cpu:.2f}, Min/Max: {min_cpu:.2f}/{max_cpu:.2f}\")\n", "\n", "# --- Run GPU Simulation via CuPy ---\n", "cp.random.seed(42)\n", "start_gpu = time.time()\n", "# Draw shape (NUM_SIMULATIONS, DOUBLINGS_REQUIRED)\n", "gauss = cp.random.standard_normal(size=(NUM_SIMULATIONS, DOUBLINGS_REQUIRED), dtype=cp.float32)\n", "# Scale & clamp\n", "times = gauss * STD_DOUBLING_TIME + MEAN_DOUBLING_TIME\n", "times_clamped = cp.clip(times, MIN_DOUBLING, MAX_DOUBLING)\n", "# Sum along axis=1 to get total per simulation\n", "results_gpu = times_clamped.sum(axis=1)\n", "cp.cuda.Stream.null.synchronize()\n", "end_gpu = time.time()\n", "gpu_time = end_gpu - start_gpu\n", "results_gpu_host = cp.asnumpy(results_gpu)\n", "\n", "# Compute GPU statistics\n", "mean_gpu = float(np.mean(results_gpu_host))\n", "median_gpu = float(np.median(results_gpu_host))\n", "min_gpu = float(np.min(results_gpu_host))\n", "max_gpu = float(np.max(results_gpu_host))\n", "\n", "print(f\"GPU: {gpu_time:.3f} s for {NUM_SIMULATIONS} sims\")\n", "print(f\"Mean (GPU): {mean_gpu:.2f}, Median (GPU): {median_gpu:.2f}, Min/Max: {min_gpu:.2f}/{max_gpu:.2f}\")\n", "\n", "# --- Plot: CPU Distribution & Stats ---\n", "plt.figure(figsize=(10, 6))\n", "plt.hist(results_cpu, bins=50, color='skyblue', edgecolor='black')\n", "plt.title(\"CPU: Distribution of Years to Reach 1GB (Monte Carlo)\")\n", "plt.xlabel(\"Years to Achieve (from 2025)\")\n", "plt.ylabel(\"Frequency\")\n", "plt.axvline(mean_cpu, color='red', linestyle='--', label=f\"Mean = {mean_cpu:.2f}\")\n", "plt.axvline(median_cpu, color='green', linestyle='--', label=f\"Median = {median_cpu:.2f}\")\n", "plt.legend()\n", "plt.show()\n", "\n", "# --- Plot: GPU Distribution & Stats ---\n", "plt.figure(figsize=(10, 6))\n", "plt.hist(results_gpu_host, bins=50, color='lightgreen', edgecolor='black')\n", "plt.title(\"GPU: Distribution of Years to Reach 1GB (Monte Carlo)\")\n", "plt.xlabel(\"Years to Achieve (from 2025)\")\n", "plt.ylabel(\"Frequency\")\n", "plt.axvline(mean_gpu, color='red', linestyle='--', label=f\"Mean = {mean_gpu:.2f}\")\n", "plt.axvline(median_gpu, color='green', linestyle='--', label=f\"Median = {median_gpu:.2f}\")\n", "plt.legend()\n", "plt.show()\n", "\n", "# --- LOWESS Smoothing on GPU Results ---\n", "sorted_gpu = np.sort(results_gpu_host)\n", "x = np.arange(NUM_SIMULATIONS)\n", "# LOWESS (CPU only)\n", "smoothed = lowess(sorted_gpu, x, frac=0.05)\n", "x_smooth = smoothed[:, 0]\n", "y_smooth = smoothed[:, 1]\n", "\n", "plt.figure(figsize=(10, 6))\n", "plt.plot(x, sorted_gpu, label='Sorted GPU Results', alpha=0.3)\n", "plt.plot(x_smooth, y_smooth, color='red', linewidth=2.0, label='LOWESS (GPU data)')\n", "plt.title(\"GPU: Sorted + LOWESS Smoothed (Years to 1GB)\")\n", "plt.xlabel(\"Simulation Index (Sorted)\")\n", "plt.ylabel(\"Years to Achieve (Ascending)\")\n", "plt.legend()\n", "plt.show()" ], "metadata": { "id": "LsueUOizXUsD", "outputId": "163af6ac-51ce-46b5-b043-b40d0c14498b", "colab": { "base_uri": "https://localhost:8080/", "height": 1000 } }, "execution_count": 12, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "CPU: 0.136 s for 10000 sims\n", "Mean (CPU): 60.23, Median (CPU): 35.19, Min/Max: 24.89/45.09\n", "GPU: 0.002 s for 10000 sims\n", "Mean (GPU): 35.03, Median (GPU): 35.02, Min/Max: 23.53/46.47\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" 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\n" 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