script

stack-info: PR: #8, branch: drisspg/stack/2

Author: drisspg

CMakeLists.txt

@@ -53,7 +53,7 @@ foreach(EXAMPLE_SOURCE ${EXAMPLE_SOURCES})
 
     # CUDA properties provided by CMAKE
     set_target_properties(${EXAMPLE_NAME} PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
-    set_target_properties(${EXAMPLE_NAME} PROPERTIES CUDA_ARCHITECTURES 100)
+    set_target_properties(${EXAMPLE_NAME} PROPERTIES CUDA_ARCHITECTURES 100a)
 
     # Convert the flags string into a list of flags
     separate_arguments(EXTRA_CUDA_FLAGS_LIST UNIX_COMMAND "${EXTRA_CUDA_FLAGS}")

examples/misc/atomic_max.cu

@@ -2,7 +2,7 @@
 #include <iostream>
 #include <limits>
 
-__device__ __forceinline__ float atomicMaxFloatBAD(float *addr, float value) {
+__device__ __forceinline__ void atomicMaxFloatBAD(float *addr, float value) {
   // source: https://stackoverflow.com/a/51549250
    (value >= 0)
              ? __int_as_float(atomicMax((int *)addr, __float_as_int(value)))

examples/test_nvfp4_rounding.cu

@@ -0,0 +1,336 @@
+// Compilation: nvcc -arch=sm_90 -std=c++17 test_nvfp4_rounding.cu -o test_nvfp4_rounding
+// For Godbolt: Add flags: -arch=sm_90 -std=c++17
+// Note: Requires SM 9.0+ for FP4 E2M1 intrinsics
+
+#include <cuda_fp16.h>
+#include <cuda_bf16.h>
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <cmath>
+#include <algorithm>
+
+// FP4 E2M1 lookup table
+const float fp4_e2m1_lut[16] = {
+    0.0f, 0.5f, 1.0f, 1.5f, 2.0f, 3.0f, 4.0f, 6.0f,
+    -0.0f, -0.5f, -1.0f, -1.5f, -2.0f, -3.0f, -4.0f, -6.0f
+};
+
+// Simple test kernel to verify PTX instruction works
+__global__ void test_ptx_instruction() {
+    // Test with known values
+    float test_vals[4] = {1.0f, 2.0f, 3.0f, 4.0f};
+    unsigned int results[4];
+
+    for (int i = 0; i < 4; i++) {
+        asm volatile (
+            "{\n\t"
+            "  .reg .b8 fp4_byte;\n\t"
+            "  cvt.rn.satfinite.e2m1x2.f32 fp4_byte, %1, %2;\n\t"
+            "  cvt.u32.u8 %0, fp4_byte;\n\t"
+            "}\n\t"
+            : "=r"(results[i])
+            : "f"(test_vals[i]), "f"(0.0f)
+        );
+    }
+
+    // Print results (only thread 0)
+    if (threadIdx.x == 0 && blockIdx.x == 0) {
+        printf("PTX Instruction Test:\n");
+        for (int i = 0; i < 4; i++) {
+            uint8_t byte = results[i] & 0xFF;
+            uint8_t low = byte & 0xF;
+            uint8_t high = (byte >> 4) & 0xF;
+            printf("  %.1f → byte: 0x%02x (low: 0x%x, high: 0x%x)\n",
+                   test_vals[i], byte, low, high);
+        }
+        printf("\n");
+    }
+}
+
+// Test kernel - correct PTX usage based on NVIDIA docs
+__global__ void test_fp4_conversion_kernel(
+    float* inputs,
+    uint8_t* fp4_outputs,
+    uint8_t* raw_bytes,
+    int count
+) {
+    int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx >= count) return;
+
+    float val1 = inputs[idx];
+    float val2 = 0.0f;  // dummy second value
+
+    // The cvt instruction outputs a single byte containing two FP4 values
+    // We need to use inline PTX with proper register declarations
+    unsigned int result = 0;
+
+    asm volatile (
+        "{\n\t"
+        "  .reg .b8 fp4_byte;\n\t"
+        "  cvt.rn.satfinite.e2m1x2.f32 fp4_byte, %1, %2;\n\t"
+        "  cvt.u32.u8 %0, fp4_byte;\n\t"  // Convert byte to 32-bit for output
+        "}\n\t"
+        : "=r"(result)
+        : "f"(val1), "f"(val2)
+    );
+
+    // Extract the byte
+    uint8_t byte_result = result & 0xFF;
+    raw_bytes[idx] = byte_result;
+
+    // The e2m1x2 format packs two FP4 values:
+    // First float → ??? (need to determine which nibble)
+    // Second float → ??? (need to determine which nibble)
+
+    // For now, store the full byte and we'll analyze it on the host
+    fp4_outputs[idx] = byte_result;
+}
+
+int main() {
+    std::cout << "Testing CUDA FP4 E2M1 Rounding Behavior\n";
+    std::cout << "=======================================\n\n";
+
+    // First, run a simple test to verify PTX instruction works
+    test_ptx_instruction<<<1, 1>>>();
+    cudaDeviceSynchronize();
+
+    // Print all possible E2M1 values
+    std::cout << "All possible FP4 E2M1 values:\n";
+    std::cout << "-----------------------------\n";
+    std::cout << "FP4   Binary   Value\n";
+    std::cout << "---   ------   -----\n";
+
+    for (uint8_t i = 0; i <= 15; i++) {
+        std::cout << "0x" << std::hex << (int)i << std::dec
+                  << "   0b" << ((i>>3)&1) << ((i>>2)&1) << ((i>>1)&1) << (i&1)
+                  << "   " << std::setw(5) << fp4_e2m1_lut[i] << "\n";
+    }
+    std::cout << "\n";
+
+    // Test values - focusing on tie cases
+    std::vector<float> test_values = {
+        // Perfect tie cases
+        0.75f,    // Exactly between 0.5 and 1.0
+        1.25f,    // Exactly between 1.0 and 1.5
+        1.75f,    // Exactly between 1.5 and 2.0
+        2.5f,     // Exactly between 2.0 and 3.0
+        3.5f,     // Exactly between 3.0 and 4.0
+        5.0f,     // Exactly between 4.0 and 6.0
+        // Negative ties
+        -0.75f, -1.25f, -1.75f, -2.5f, -3.5f, -5.0f,
+        // Non-ties for comparison
+        0.6f, 1.1f, 2.2f, 2.8f
+    };
+
+    // Allocate memory
+    float* d_inputs;
+    uint8_t* d_outputs;
+    uint8_t* d_raw_bytes;
+    cudaMalloc(&d_inputs, test_values.size() * sizeof(float));
+    cudaMalloc(&d_outputs, test_values.size() * sizeof(uint8_t));
+    cudaMalloc(&d_raw_bytes, test_values.size() * sizeof(uint8_t));
+
+    // Copy inputs
+    cudaMemcpy(d_inputs, test_values.data(),
+               test_values.size() * sizeof(float),
+               cudaMemcpyHostToDevice);
+
+    // Run kernel
+    int threads = 256;
+    int blocks = (test_values.size() + threads - 1) / threads;
+    test_fp4_conversion_kernel<<<blocks, threads>>>(d_inputs, d_outputs, d_raw_bytes, test_values.size());
+    cudaDeviceSynchronize();
+
+    // Get results
+    std::vector<uint8_t> h_outputs(test_values.size());
+    std::vector<uint8_t> h_raw_bytes(test_values.size());
+    cudaMemcpy(h_outputs.data(), d_outputs,
+               h_outputs.size() * sizeof(uint8_t),
+               cudaMemcpyDeviceToHost);
+    cudaMemcpy(h_raw_bytes.data(), d_raw_bytes,
+               h_raw_bytes.size() * sizeof(uint8_t),
+               cudaMemcpyDeviceToHost);
+
+    // Debug: Show raw bytes and figure out nibble ordering
+    std::cout << "\nDebug: Raw bytes from PTX instruction:\n";
+    std::cout << "--------------------------------------\n";
+
+    for (size_t i = 0; i < 6 && i < test_values.size(); i++) {
+        uint8_t raw = h_raw_bytes[i];
+        uint8_t low = raw & 0xF;
+        uint8_t high = (raw >> 4) & 0xF;
+
+        std::cout << "Input: " << std::setw(6) << test_values[i]
+                  << " → Raw byte: 0x" << std::hex << std::setw(2) << std::setfill('0') << (int)raw << std::dec;
+
+        float decoded_low = fp4_e2m1_lut[low];
+        float decoded_high = fp4_e2m1_lut[high];
+        float error_low = std::abs(test_values[i] - decoded_low);
+        float error_high = std::abs(test_values[i] - decoded_high);
+
+        std::cout << "\n  Low nibble:  0x" << std::hex << (int)low << std::dec
+                  << " = " << std::setw(5) << decoded_low
+                  << " (error: " << error_low << ")";
+        if (error_low < error_high) std::cout << " ← likely match";
+
+        std::cout << "\n  High nibble: 0x" << std::hex << (int)high << std::dec
+                  << " = " << std::setw(5) << decoded_high
+                  << " (error: " << error_high << ")";
+        if (error_high < error_low) std::cout << " ← likely match";
+
+        std::cout << std::setfill(' ') << "\n\n";
+    }
+
+    // Determine which nibble to use based on errors
+    std::cout << "Determining nibble assignment...\n";
+    float total_error_low = 0, total_error_high = 0;
+    int count_low_better = 0, count_high_better = 0;
+
+    for (size_t i = 0; i < test_values.size(); i++) {
+        uint8_t raw = h_raw_bytes[i];
+        uint8_t low = raw & 0xF;
+        uint8_t high = (raw >> 4) & 0xF;
+
+        float error_low = std::abs(test_values[i] - fp4_e2m1_lut[low]);
+        float error_high = std::abs(test_values[i] - fp4_e2m1_lut[high]);
+
+        total_error_low += error_low;
+        total_error_high += error_high;
+
+        if (error_low < error_high) count_low_better++;
+        else if (error_high < error_low) count_high_better++;
+    }
+
+    bool use_low_nibble = (total_error_low <= total_error_high);
+    std::cout << "Total error using low nibble: " << total_error_low << "\n";
+    std::cout << "Total error using high nibble: " << total_error_high << "\n";
+    std::cout << "Decision: Use " << (use_low_nibble ? "LOW" : "HIGH") << " nibble for first float\n\n";
+
+    // Update outputs based on decision
+    for (size_t i = 0; i < h_outputs.size(); i++) {
+        if (use_low_nibble) {
+            h_outputs[i] = h_raw_bytes[i] & 0xF;
+        } else {
+            h_outputs[i] = (h_raw_bytes[i] >> 4) & 0xF;
+        }
+    }
+
+    // Analyze results
+    std::cout << "Conversion Results:\n";
+    std::cout << "==================\n";
+    std::cout << std::setw(8) << "Input"
+              << std::setw(8) << "FP4"
+              << std::setw(10) << "Decoded"
+              << std::setw(10) << "Error"
+              << std::setw(20) << "Comment\n";
+
+    for (size_t i = 0; i < test_values.size(); i++) {
+        float input = test_values[i];
+        uint8_t fp4 = h_outputs[i];
+        float decoded = fp4_e2m1_lut[fp4];
+        float error = std::abs(input - decoded);
+
+        std::cout << std::fixed << std::setprecision(3);
+        std::cout << std::setw(8) << input
+                  << std::setw(8) << "0x" << std::hex << (int)fp4 << std::dec
+                  << std::setw(10) << decoded
+                  << std::setw(10) << error;
+
+        // Check for tie cases
+        bool is_tie = false;
+        float option1 = 0, option2 = 0;
+        for (int j = 0; j < 16; j++) {
+            for (int k = j+1; k < 16; k++) {
+                if (std::abs(std::abs(input - fp4_e2m1_lut[j]) -
+                            std::abs(input - fp4_e2m1_lut[k])) < 1e-6f &&
+                    std::abs(input - fp4_e2m1_lut[j]) < 0.51f) {
+                    is_tie = true;
+                    option1 = fp4_e2m1_lut[j];
+                    option2 = fp4_e2m1_lut[k];
+                    if (option1 > option2) std::swap(option1, option2);
+                }
+            }
+        }
+
+        if (is_tie) {
+            std::cout << " (tie: " << option1 << " vs " << option2 << ")";
+        }
+        std::cout << "\n";
+    }
+
+    // Detailed tie analysis
+    std::cout << "\n\nTie-Breaking Analysis:\n";
+    std::cout << "=====================\n";
+    std::cout << "For round-to-nearest-even, ties should go to the value with even mantissa (m=0)\n\n";
+
+    std::cout << std::setw(8) << "Input"
+              << std::setw(15) << "Options"
+              << std::setw(10) << "Result"
+              << std::setw(10) << "Mantissa"
+              << std::setw(20) << "Round-to-even?\n";
+
+    // Analyze specific tie cases
+    std::vector<float> tie_values = {0.75f, 1.25f, 1.75f, 2.5f, 3.5f, 5.0f};
+    std::vector<std::pair<float, float>> tie_options = {
+        {0.5f, 1.0f}, {1.0f, 1.5f}, {1.5f, 2.0f},
+        {2.0f, 3.0f}, {3.0f, 4.0f}, {4.0f, 6.0f}
+    };
+
+    for (size_t i = 0; i < tie_values.size(); i++) {
+        // Find the result in our test
+        for (size_t j = 0; j < test_values.size(); j++) {
+            if (std::abs(test_values[j] - tie_values[i]) < 1e-6f) {
+                uint8_t fp4 = h_outputs[j];
+                float decoded = fp4_e2m1_lut[fp4];
+                int mantissa = fp4 & 1;
+
+                std::cout << std::setw(8) << tie_values[i]
+                          << std::setw(15) << tie_options[i].first
+                          << " vs " << tie_options[i].second
+                          << std::setw(10) << decoded
+                          << std::setw(10) << "m=" << mantissa
+                          << std::setw(20) << (mantissa == 0 ? "Yes ✓" : "No ✗")
+                          << "\n";
+                break;
+            }
+        }
+    }
+
+    // Special focus on 2.5
+    std::cout << "\n\n2.5 Detailed Analysis:\n";
+    std::cout << "=====================\n";
+    for (size_t i = 0; i < test_values.size(); i++) {
+        if (std::abs(test_values[i] - 2.5f) < 1e-6f) {
+            uint8_t fp4 = h_outputs[i];
+            float decoded = fp4_e2m1_lut[fp4];
+
+            std::cout << "Input: 2.5\n";
+            std::cout << "FP4 encoding: 0x" << std::hex << (int)fp4 << std::dec
+                      << " (0b" << ((fp4>>3)&1) << ((fp4>>2)&1)
+                      << ((fp4>>1)&1) << (fp4&1) << ")\n";
+            std::cout << "Decoded value: " << decoded << "\n";
+            std::cout << "Mantissa bit: " << (fp4 & 1) << "\n\n";
+
+            std::cout << "Options were:\n";
+            std::cout << "  2.0 (0x4, m=0) - even mantissa\n";
+            std::cout << "  3.0 (0x5, m=1) - odd mantissa\n\n";
+
+            if (fp4 == 0x4) {
+                std::cout << "✓ Correctly rounded to even (2.0)\n";
+            } else if (fp4 == 0x5) {
+                std::cout << "✗ Rounded to odd (3.0) - NOT round-to-nearest-even\n";
+            } else {
+                std::cout << "! Unexpected result\n";
+            }
+            break;
+        }
+    }
+
+    // Cleanup
+    cudaFree(d_inputs);
+    cudaFree(d_outputs);
+    cudaFree(d_raw_bytes);
+
+    return 0;
+}