Update TensorRT README.md

hpvm/projects/hpvm-tensor-rt/README.md

@@ -10,7 +10,7 @@
 ## Building Tensor Runtime
 
 Tensor Runtime and the DNN sources using the Tensor runtime are built with the unified HPVM build system. These 
-can also be separately built. HPVM Tensor Runtime can be built as:
+can also be separately built. HPVM Tensor Runtime can be built under the `build` directory as:
 
 ```
 make -j ${NUM_THREADS} tensor_runtime
@@ -18,17 +18,34 @@ make -j ${NUM_THREADS} tensor_runtime
 
 The tensor runtime is built as a static library under `build/lib/liibtensor_runtime.a` 
 
+### TensorRT DNN Benchmarks
 
-## Tensor Runtime APIs
+To assist development of tensor-based programs using only the tensor runtime, we include 
+sources under `dnn_sources` that directly invoke the HPVM Tensor Runtime API calls for tensor operations, e.g., convolution, matrix multiplication, 
+add, relu, among others.
 
+Each benchmark can be build under your `build` directory as:
 
-- For examples of using `tensor_runtime` functions, see `dnn_sources/src/alexnet_cifar10.cc`.
-  - Also, try running `build/alexnet_cifar10` which is compiled from that file and runnable out of the box.
-
-
-## Directory Structure
-
-- `tensor_runtime`:
-  
-- `dnn_sources`:
+```
+make -j ${NUM_THREADS} ${BENCHMARK}
+``` 
+
+Currently, 17 Benchmarks included:
+
+|                        |                        |
+|------------------------|------------------------|
+| lenet_mnist_fp32       | lenet_mnist_fp16       |
+| alexnet_cifar10_fp32   | alexnet_cifar10_fp16   |
+| alexnet2_cifar10_fp32  | alexnet2_cifar10_fp16  |
+| vgg16_cifar10_fp32     | vgg16_cifar10_fp16     |
+| vgg16_cifar100_fp32    | vgg16_cifar100_fp16    |
+| mobilenet_cifar10_fp32 | mobilenet_cifar10_fp16 |
+| resnet18_cifar10_fp32  | resnet18_cifar10_fp16  |
+| alexnet_imagenet_fp32  |                        |
+| vgg16_imagenet_fp32    |                        |
+| resnet50_imagenet_fp32 |                        |
+
+`_fp32` suffix denotes fp32 binaries - these use the FP32 API calls 
+
+`_fp_16` suffix denotes fp16 binaries - these use FP16 (half precision) calls.