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// SPDX-License-Identifier: BSD-3-Clause
/*
* multikernel.cu - dependent three-kernel sequence over 1M floats.
*
* Three different kernels run one after another with a data dependency, each
* result verified on the host before the next stage starts:
*
* stage 1 add c[i] = a[i] + b[i]
* stage 2 scale c[i] = c[i] * 3
* stage 3 saxpy out[i] = 1.5 * c[i] + d[i]
*
* All inputs are exact binary fractions, so the host model is bit-exact and
* any mismatch is a real device-side divergence.
*
* Output lines are stable and greppable:
*
* DEVICE <name> cc=<major>.<minor> sm=<count> mem=<bytes>
* STAGE idx=<n> name=<add|scale|saxpy> bad=<mismatches>
* MULTI stages=3 bad=<mismatches>
* STATUS OK|FAIL
*
* Build with a static CUDA runtime (--cudart=static) so the guest only needs
* the driver's libcuda.so, not a CUDA toolkit installation:
*
* nvcc -O2 --cudart=static -o multikernel multikernel.cu
*
* Then, from the guest: /tmp/multikernel
*/
#include <cstdio>
#include <cstdlib>
#include <cstdint>
#include <cuda_runtime.h>
#define CHECK(x) \
do { \
cudaError_t e_ = (x); \
if (e_ != cudaSuccess) { \
printf("CUDA_ERROR %s at line %d\n", \
cudaGetErrorString(e_), __LINE__); \
printf("STATUS FAIL\n"); \
return 1; \
} \
} while (0)
__global__ void k_add(const float *a, const float *b, float *c, int n)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < n)
c[i] = a[i] + b[i];
}
__global__ void k_scale(float *c, float s, int n)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < n)
c[i] = c[i] * s;
}
__global__ void k_saxpy(const float *x, const float *y, float *out,
float alpha, int n)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < n)
out[i] = alpha * x[i] + y[i];
}
static int verify_stage(const float *got, const float *a, const float *b,
const float *d, float scale, float alpha, int n,
int stage)
{
float *exp = (float *)malloc((size_t)n * sizeof(float));
int i, bad = 0;
const char *name = stage == 1 ? "add" : stage == 2 ? "scale" : "saxpy";
if (!exp)
return -1;
/* Host reference model, matching the kernel chain exactly. */
for (i = 0; i < n; i++) {
float v = a[i] + b[i];
if (stage >= 2)
v = v * scale;
if (stage >= 3)
v = alpha * v + d[i];
exp[i] = v;
}
for (i = 0; i < n; i++) {
if (got[i] != exp[i])
bad++;
}
printf("STAGE idx=%d name=%s bad=%d\n", stage, name, bad);
free(exp);
return bad;
}
int main(void)
{
cudaDeviceProp prop;
const int n = 1 << 20; /* 1M floats */
const float scale = 3.0f, alpha = 1.5f;
size_t bytes = (size_t)n * sizeof(float);
float *h_a, *h_b, *h_c, *h_d, *h_out;
float *d_a, *d_b, *d_c, *d_d, *d_out;
int bad = 0, i, s;
const int grid = (n + 255) / 256;
setvbuf(stdout, NULL, _IONBF, 0);
CHECK(cudaGetDeviceProperties(&prop, 0));
printf("DEVICE %s cc=%d.%d sm=%d mem=%llu\n", prop.name,
prop.major, prop.minor, prop.multiProcessorCount,
(unsigned long long)prop.totalGlobalMem);
h_a = (float *)malloc(bytes);
h_b = (float *)malloc(bytes);
h_c = (float *)malloc(bytes);
h_d = (float *)malloc(bytes);
h_out = (float *)malloc(bytes);
if (!h_a || !h_b || !h_c || !h_d || !h_out)
return 1;
for (i = 0; i < n; i++) {
h_a[i] = (float)(i % 1000) * 0.5f;
h_b[i] = (float)(i % 997) * 0.25f;
h_d[i] = (float)(i % 89) * 0.125f;
}
CHECK(cudaMalloc(&d_a, bytes));
CHECK(cudaMalloc(&d_b, bytes));
CHECK(cudaMalloc(&d_c, bytes));
CHECK(cudaMalloc(&d_d, bytes));
CHECK(cudaMalloc(&d_out, bytes));
CHECK(cudaMemcpy(d_a, h_a, bytes, cudaMemcpyHostToDevice));
CHECK(cudaMemcpy(d_b, h_b, bytes, cudaMemcpyHostToDevice));
CHECK(cudaMemcpy(d_d, h_d, bytes, cudaMemcpyHostToDevice));
/* stage 1: add */
k_add<<<grid, 256>>>(d_a, d_b, d_c, n);
CHECK(cudaGetLastError());
CHECK(cudaDeviceSynchronize());
CHECK(cudaMemcpy(h_c, d_c, bytes, cudaMemcpyDeviceToHost));
s = verify_stage(h_c, h_a, h_b, h_d, scale, alpha, n, 1);
if (s < 0)
return 1;
bad += s;
/* stage 2: scale (depends on stage 1's c) */
k_scale<<<grid, 256>>>(d_c, scale, n);
CHECK(cudaGetLastError());
CHECK(cudaDeviceSynchronize());
CHECK(cudaMemcpy(h_c, d_c, bytes, cudaMemcpyDeviceToHost));
s = verify_stage(h_c, h_a, h_b, h_d, scale, alpha, n, 2);
if (s < 0)
return 1;
bad += s;
/* stage 3: saxpy out = alpha * c + d (depends on stage 2's c) */
k_saxpy<<<grid, 256>>>(d_c, d_d, d_out, alpha, n);
CHECK(cudaGetLastError());
CHECK(cudaDeviceSynchronize());
CHECK(cudaMemcpy(h_out, d_out, bytes, cudaMemcpyDeviceToHost));
s = verify_stage(h_out, h_a, h_b, h_d, scale, alpha, n, 3);
if (s < 0)
return 1;
bad += s;
printf("MULTI stages=3 bad=%d\n", bad);
if (bad != 0) {
printf("STATUS FAIL\n");
return 1;
}
printf("STATUS OK\n");
CHECK(cudaFree(d_a));
CHECK(cudaFree(d_b));
CHECK(cudaFree(d_c));
CHECK(cudaFree(d_d));
CHECK(cudaFree(d_out));
free(h_a);
free(h_b);
free(h_c);
free(h_d);
free(h_out);
return 0;
}
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