CPU KV Offloading: Use more CUDA streams (#29013)

Signed-off-by: Or Ozeri <oro@il.ibm.com>

tests/v1/kv_offload/test_cpu_gpu.py

@@ -9,7 +9,7 @@ import torch
 from vllm.platforms import current_platform
 from vllm.v1.attention.backends.flash_attn import FlashAttentionBackend
 from vllm.v1.kv_offload.mediums import CPULoadStoreSpec, GPULoadStoreSpec
-from vllm.v1.kv_offload.worker.cpu_gpu import CpuGpuOffloadingHandler
+from vllm.v1.kv_offload.worker.cpu_gpu import CpuGpuOffloadingHandlers
 
 BACKENDS_TO_TEST = [FlashAttentionBackend]
 
@@ -82,7 +82,7 @@ def test_transfer(
 
     # create handler
     cpu_block_size = gpu_blocks_per_cpu_block * gpu_block_size
-    handler = CpuGpuOffloadingHandler(
+    handlers = CpuGpuOffloadingHandlers(
         attn_backends=attn_backends,
         gpu_block_size=gpu_block_size,
         cpu_block_size=cpu_block_size,
@@ -112,8 +112,7 @@ def test_transfer(
 
     # set transfer direction
     if gpu_to_cpu:
-        src_kv_caches = handler.gpu_tensors
-        dst_kv_caches = handler.cpu_tensors
+        handler = handlers.gpu_to_cpu_handler
         src_spec_class = GPULoadStoreSpec
         dst_spec_class = CPULoadStoreSpec
         src_blocks = gpu_blocks
@@ -122,8 +121,7 @@ def test_transfer(
         dst_blocks_in_gpu_block_size = cpu_blocks_in_gpu_block_size
         dst_size_in_gpu_blocks = num_cpu_blocks * gpu_blocks_per_cpu_block
     else:
-        src_kv_caches = handler.cpu_tensors
-        dst_kv_caches = handler.gpu_tensors
+        handler = handlers.cpu_to_gpu_handler
         src_spec_class = CPULoadStoreSpec
         dst_spec_class = GPULoadStoreSpec
         src_blocks = cpu_blocks
@@ -144,12 +142,12 @@ def test_transfer(
     dst_spec = dst_spec_class(dst_blocks)
 
     # clone src and dst tensors before transfer
-    orig_src_caches = [x.clone() for x in src_kv_caches]
-    orig_dst_caches = [x.clone() for x in dst_kv_caches]
+    orig_src_caches = [x.clone() for x in handler.src_tensors]
+    orig_dst_caches = [x.clone() for x in handler.dst_tensors]
 
     # call transfer function
     assert handler.transfer_async(1, (src_spec, dst_spec))
-    assert set(handler.transfer_events.keys()) == {1}
+    assert set({x[0] for x in handler._transfers}) == {1}
 
     # wait for transfer to complete
     end_time = time.time() + 10
@@ -161,15 +159,15 @@ def test_transfer(
         time.sleep(0.1)
 
     # verify src tensors did not change
-    for orig_tensor, tensor in zip(orig_src_caches, src_kv_caches):
+    for orig_tensor, tensor in zip(orig_src_caches, handler.src_tensors):
         assert torch.equal(orig_tensor, tensor)
 
     # verify dst tensors
     for dst_block in range(dst_size_in_gpu_blocks):
         src_block_candidate = dst_to_src.get(dst_block)
         for src_cache, dst_cache, orig_dst_cache, kv_dim in zip(
-            src_kv_caches,
-            dst_kv_caches,
+            handler.src_tensors,
+            handler.dst_tensors,
             orig_dst_caches,
             handler.kv_dim_before_num_blocks,
         ):