Add LRC microbenchmarks for L2 request coalescing analysis

.gitignore

@@ -24,4 +24,12 @@ tmp/
 src/cuda/GPU_Microbenchmark/ubench/**/*
 !src/cuda/GPU_Microbenchmark/ubench/**/*/
 !src/cuda/GPU_Microbenchmark/ubench/**/*.*
-!src/cuda/GPU_Microbenchmark/ubench/**/Makefile
+!src/cuda/GPU_Microbenchmark/ubench/**/Makefile
+
+# IDE/AI tool related files
+.vscode/
+.cursor/
+.cursorrules
+.claude/
+CLAUDE.md
+.clangd

src/cuda/GPU_Microbenchmark/ubench/lrc/lrc_max_merged/Makefile

@@ -0,0 +1,14 @@
+SRC = lrc_max_merged.cu
+
+EXE = lrc_max_merged
+
+# NVCC_FLGAS = -Xptxas -dlcm=cg -Xptxas -dscm=wt
+# LRC is supported on SM_90 and above
+ARCH?=sm_90a sm_100a sm_101 sm_120 
+# Unset the CUDA_CPPFLAGS which is set based on CUDA version
+# but LRC is only supported on SM_90 and above
+CUDA_CPPFLAGS=
+# Generate code for both sm_XXX and compute_XXX (SASS and PTX)
+NVCC_FLAGS := $(foreach arch,$(ARCH),-gencode=arch=compute_$(subst sm_,,$(arch)),code=$(arch) -gencode=arch=compute_$(subst sm_,,$(arch)),code=compute_$(subst sm_,,$(arch))) -std=c++17 -O0
+
+include ../../../common/common.mk

src/cuda/GPU_Microbenchmark/ubench/lrc/lrc_max_merged/lrc_max_merged.cu

@@ -0,0 +1,283 @@
+// LRC Max Merged Microbenchmark
+// Use mbarrier and threadblock cluster to ensure
+// best synchronization among warps sending request
+// to the same L2 sector
+
+#include <assert.h>
+#include <bits/getopt_core.h>
+#include <cstdint>
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include "../../../hw_def/common/gpuConfig.h"
+#include "../../../hw_def/hw_def.h"
+
+#include <cuda.h>
+#include <cuda/ptx>
+#include <cooperative_groups.h>
+namespace cg = cooperative_groups;
+
+/**
+ * @brief Synchronize within a cluster using mbarrier
+ * 
+ * @return
+ */
+__device__ __forceinline__ void sync_cluster(void) {
+  /**
+   * Synchronization
+   */
+  // Initialize mbarrier
+  #pragma nv_diag_suppress static_var_with_dynamic_init
+  __shared__ uint64_t bar;
+  // Barrier handles
+  uint64_t *clusterleader_bar_handle;
+  uint64_t *local_bar_handle;
+
+  // Setup remote barrier address
+  cg::cluster_group cluster = cg::this_cluster();
+  unsigned int clusterBlockRank = cluster.block_rank();
+  unsigned int clusterSize = cluster.dim_blocks().x;
+
+  // Check if this threadblock is the cluster leader
+  bool isClusterLeader = clusterBlockRank == 0;
+  // Check if this thread is the thread leader
+  bool isThreadLeader = threadIdx.x == 0;
+
+  // Only cluster leader should initialize the barrier
+  // other threadblocks should use remote barrier address
+  if (isClusterLeader) {
+    // Get total number of threads in the cluster
+    unsigned int totalThreads = cluster.num_threads();
+
+    // Only one thread should initialize the barrier
+    if (isThreadLeader) {
+      cuda::ptx::mbarrier_init(&bar, totalThreads);
+    }
+    __syncthreads();
+    clusterleader_bar_handle = &bar;
+    local_bar_handle = &bar;
+  } else {
+    // Other threadblocks should init local barrier
+    // to wait for clusterleader's signal that all threadblocks
+    // have arrived
+    if (isThreadLeader) {
+      cuda::ptx::mbarrier_init(&bar, 1);
+    }
+    __syncthreads();
+    clusterleader_bar_handle = cluster.map_shared_rank(&bar, 0);
+    local_bar_handle = &bar;
+  }
+
+  // Here is the synchronization part
+  // 1. All threads in the cluster should arrive at the clusterleader's barrier
+  // 2. Since mbarrier only supports waiting on local barrier:
+  //    1. ClusterLeader will wait on its barrier that get released when all threadblocks have arrived
+  //    2. Other threadblocks will wait on their local barrier that get released when clusterleader release its barrier
+  // 3. Once clusterleader's barrier is released, all other threadblocks should launch the load to same sector address
+
+  // First all threads arrive at the clusterleader's barrier
+  cuda::ptx::mbarrier_arrive(cuda::ptx::sem_release, cuda::ptx::scope_cluster, cuda::ptx::space_cluster, clusterleader_bar_handle, 1);
+
+  // Then based on the role, we will either wait on the barrier or release the barrier
+  if (isClusterLeader) {
+    // ClusterLeader will wait on its barrier that get released when all threadblocks have arrived
+    while (!cuda::ptx::mbarrier_test_wait_parity(cuda::ptx::sem_acquire, cuda::ptx::scope_cluster, clusterleader_bar_handle, 0)) {}
+
+    // Now ClusterLeader should release other threadblocks to proceed, we will execute this in a single warp
+    // for each threadblock, we will release its barrier
+    if (threadIdx.x < clusterSize && threadIdx.x != clusterBlockRank) {
+      uint64_t *remote_bar_handle = cluster.map_shared_rank(&bar, threadIdx.x);
+      cuda::ptx::mbarrier_arrive(cuda::ptx::sem_release, cuda::ptx::scope_cluster, cuda::ptx::space_cluster, remote_bar_handle, 1);
+    }
+  } else {
+    // Other threadblocks will wait on their local barrier that get released when clusterleader release its barrier
+    while (!cuda::ptx::mbarrier_test_wait_parity(cuda::ptx::sem_acquire, cuda::ptx::scope_cluster, local_bar_handle, 0)) {}
+  }
+  __syncthreads();
+}
+
+/**
+ * @brief Kernel to test LRC maximum merged count per entry
+ * 
+ * @param data Same sector data for all warps to access for LRC merge
+ * @param dsink Global sink to avoid optimization
+ * @return __global__ 
+ */
+__global__ void lrc_max_merged_kernel(uint64_t *data, uint64_t *dsink, unsigned active_threads_per_cluster) {
+  // The LRC max merged count should be reflected from NCU metrics
+
+  // Shmem buffer
+  __shared__ volatile uint64_t smem_buffer[16];
+
+  // Get thread index within a cluster
+  cg::cluster_group cluster = cg::this_cluster();
+  unsigned thread_within_cluster = cluster.thread_rank();
+
+  // Synchronize within a cluster
+  // If threadblocks are within the same GPC, they will be relatively in sync
+  // anyway
+  // sync_cluster();
+
+  /**
+   * LRC max merged test
+   */
+  // Now threadblocks within a cluster should be relatively in sync for testing LRC coalescing
+  // Load the same sector data into shared memory
+  // Use ld.global.cg to bypass L1 cache MSHR
+  // Send down one sector per warp, make this explicit despite in
+  // hardware with this "if", loads are still coalesced into 1 sector
+  if (thread_within_cluster < active_threads_per_cluster) {
+    // Only one sector access per warp
+    if (threadIdx.x % 32 == 0) {
+      uint64_t data_value;
+      asm volatile("{\t\n"
+                  "ld.global.cg.u64 %0, [%1];\n\t"
+                  "}"
+                  : "=l"(data_value)
+                  : "l"(&data[0]));
+      smem_buffer[0] = data_value;
+    }
+  }
+  __syncthreads();
+
+  // Write to global sink to prevent optimization
+  dsink[0] = smem_buffer[0];
+}
+
+__global__ void lrc_max_merged_kernel_cooperative(uint64_t *data, uint64_t *dsink) {
+  __shared__ volatile uint64_t smem_buffer[16];
+
+  // Global synchronization for all blocks in the grid
+  cg::grid_group grid = cg::this_grid();
+  grid.sync();
+
+  if (threadIdx.x % 32 == 0) {
+    uint64_t data_value;
+    asm volatile("{\t\n"
+                "ld.global.cg.u64 %0, [%1];\n\t"
+                "}"
+                : "=l"(data_value)
+                : "l"(&data[0]));
+    smem_buffer[0] = data_value;
+  }
+  __syncthreads();
+
+  // Write to global sink to prevent optimization
+  dsink[0] = smem_buffer[0];
+}
+
+int main(int argc, char *argv[]) {
+  initializeDeviceProp(0, argc, argv);
+  enum KernelLaunchMode {
+    NORMAL = 0,
+    CLUSTER = 1,
+    COOPERATIVE = 2,
+  };
+  const char *launch_mode_str[] = {
+    "NORMAL",
+    "CLUSTER",
+    "COOPERATIVE",
+  };
+
+  // Size of threadblock cluster
+  const unsigned MAX_CLUSTER_SIZE = 16;
+  unsigned N = MAX_CLUSTER_SIZE;
+  unsigned cluster_size = MAX_CLUSTER_SIZE;
+  unsigned threads_per_block = 256;
+  bool provide_active_threads_per_cluster = false;
+  unsigned active_threads_per_cluster = cluster_size * threads_per_block;
+  KernelLaunchMode launch_mode = NORMAL;
+  const char *optstring = "N:C:T:A:m:";
+  // CLI parsing
+  int opt;
+  while ((opt = getopt(argc, argv, optstring)) != -1) {
+    switch (opt) {
+      case 'N':
+        N = atoi(optarg);
+        break;
+      case 'C':
+        cluster_size = atoi(optarg);
+        assert(cluster_size <= MAX_CLUSTER_SIZE && "cluster_size is out of range, must be less than 16 on Hopper");
+        break;
+      case 'T':
+        threads_per_block = atoi(optarg);
+        break;
+      case 'A':
+        active_threads_per_cluster = atoi(optarg);
+        provide_active_threads_per_cluster = true;
+        break;
+      case 'm':
+        launch_mode = static_cast<KernelLaunchMode>(atoi(optarg));
+        assert(launch_mode == NORMAL || launch_mode == CLUSTER || launch_mode == COOPERATIVE && "launch_mode must be 0 (NORMAL), 1 (CLUSTER), or 2 (COOPERATIVE)");
+        break;
+      default:
+        printf("Usage: %s -N <number of threadblocks:default=16> -C <cluster_size:default=16> -T <threads_per_block:default=256> -A <active_threads_per_cluster:default=256> -m <launch_mode:default=0 (NORMAL), 1 (CLUSTER), or 2 (COOPERATIVE)>\n", argv[0]);
+        return 1;
+    }
+  }
+
+  if (!provide_active_threads_per_cluster) {
+    // Default to all threads in a cluster
+    active_threads_per_cluster = cluster_size * threads_per_block;
+  }
+
+  if (launch_mode == CLUSTER || launch_mode == NORMAL) {
+    assert(active_threads_per_cluster <= cluster_size * threads_per_block && "active_threads_per_cluster is out of range, must be less than cluster_size * threads_per_block");
+  }
+
+  // Initialize the data and global sink with single value
+  uint64_t *data_g;
+  gpuErrchk(cudaMalloc(&data_g, sizeof(uint64_t)));
+  gpuErrchk(cudaMemset(data_g, 0, sizeof(uint64_t)));
+  uint64_t *dsink_g;
+  gpuErrchk(cudaMalloc(&dsink_g, sizeof(uint64_t)));
+  gpuErrchk(cudaMemset(dsink_g, 0, sizeof(uint64_t)));
+
+  printf("=== LRC Max Merged ===\n");
+  unsigned num_cluster = launch_mode == CLUSTER ? N / cluster_size : N;
+  unsigned max_concurrent_access = active_threads_per_cluster / 32 * num_cluster;
+  printf("N_BLOCKS=%u, THREADS_PER_BLOCK=%u, MAX_CONCURRENT_ACCESS=%u, LAUNCH_MODE=%s\n", N, threads_per_block, max_concurrent_access, launch_mode_str[launch_mode]);
+  if (launch_mode == CLUSTER) {
+    printf("CLUSTER_SIZE=%u\n", cluster_size);
+  }
+  printf("Profile with ncu to measure LRC max merged count.\n");
+
+  if (launch_mode == CLUSTER) {
+    printf("Launching with threadblock cluster to schedule threadblocks in the same GPC...\n");
+    // Launch configurable cluster shape
+    // Enable upto 16 cluster size
+    gpuErrchk(cudaFuncSetAttribute(lrc_max_merged_kernel, cudaFuncAttributeNonPortableClusterSizeAllowed, 1));
+    // Kernel launch configuration
+    cudaLaunchConfig_t config = {0};
+    config.gridDim          = dim3{N};  // N blocks
+    config.blockDim         = dim3{threads_per_block}; // threads_per_block threads per block
+    cudaLaunchAttribute attribute[1];
+    attribute[0].id               = cudaLaunchAttributeClusterDimension;
+    attribute[0].val.clusterDim.x = cluster_size; // Cluster size is also Nx1x1
+    attribute[0].val.clusterDim.y = 1;
+    attribute[0].val.clusterDim.z = 1;
+    config.attrs    = attribute;
+    config.numAttrs = 1;
+
+    cudaLaunchKernelEx(&config, lrc_max_merged_kernel, data_g, dsink_g, active_threads_per_cluster);
+  } else if (launch_mode == NORMAL) {
+    printf("Launching threadblocks normally...\n");
+    lrc_max_merged_kernel<<<N, threads_per_block>>>(data_g, dsink_g, active_threads_per_cluster);
+  } else if (launch_mode == COOPERATIVE) {
+    printf("Launching with cooperative kernel...\n");
+    void *kernelArgs[] = {(void *)&data_g, (void *)&dsink_g};
+    gpuErrchk(cudaLaunchCooperativeKernel(
+        (void *)lrc_max_merged_kernel_cooperative, N, threads_per_block, kernelArgs));
+  }
+
+  gpuErrchk(cudaPeekAtLastError());
+  gpuErrchk(cudaDeviceSynchronize());
+
+  printf("Kernel completed. Use ncu to analyze LRC max merged count.\n");
+
+  // Cleanup
+  cudaFree(data_g);
+  cudaFree(dsink_g);
+
+  return 0;
+}

src/cuda/GPU_Microbenchmark/ubench/lrc/lrc_max_merged/run_lrc_merged.sh

@@ -0,0 +1,10 @@
+#!/bin/bash
+export CUDA_VISIBLE_DEVICES=7
+
+# Measure maximum merge count per LRC entry
+# Run with cluster launch with 8 threadblocks and 8 threadblocks per cluster
+# Should see 8*128/32 = 32 sectors request issued from SM
+# and 8 sectors request issued from L2 cache
+TMPDIR=./ ncu \
+	--metrics l1tex__t_requests_pipe_lsu_mem_global_op_ld.sum,l1tex__t_sectors_pipe_lsu_mem_global_op_ld.sum,lts__t_sectors_srcunit_tex_op_read.sum,lts__t_sectors_srcunit_tex_op_read_lookup_hit.sum,lts__t_sectors_srcunit_tex_op_read_lookup_miss.sum \
+	--replay-mode application ./lrc_max_merged -N 8 -C 8 -T 128 -m 1

src/cuda/GPU_Microbenchmark/ubench/lrc/lrc_merge_size/Makefile

@@ -0,0 +1,14 @@
+SRC = lrc_merge_size.cu
+
+EXE = lrc_merge_size
+
+# NVCC_FLGAS = -Xptxas -dlcm=cg -Xptxas -dscm=wt
+# LRC is supported on SM_90 and above
+ARCH?=sm_90a sm_100a sm_101 sm_120 
+# Unset the CUDA_CPPFLAGS which is set based on CUDA version
+# but LRC is only supported on SM_90 and above
+CUDA_CPPFLAGS=
+# Generate code for both sm_XXX and compute_XXX (SASS and PTX)
+NVCC_FLAGS := $(foreach arch,$(ARCH),-gencode=arch=compute_$(subst sm_,,$(arch)),code=$(arch) -gencode=arch=compute_$(subst sm_,,$(arch)),code=compute_$(subst sm_,,$(arch))) -std=c++17 -O0
+
+include ../../../common/common.mk